{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Table of Contents](./table_of_contents.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Extended Kalman Filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import division, print_function\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <style>\n",
       "        .output_wrapper, .output {\n",
       "            height:auto !important;\n",
       "            max-height:10000px; \n",
       "        }\n",
       "        .output_scroll {\n",
       "            box-shadow:none !important;\n",
       "            webkit-box-shadow:none !important;\n",
       "        }\n",
       "        </style>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#format the book\n",
    "import book_format\n",
    "book_format.set_style()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have developed the theory for the linear Kalman filter. Then, in the last two chapters we broached the topic of using Kalman filters for nonlinear problems. In this chapter we will learn the Extended Kalman filter (EKF). The EKF handles nonlinearity by linearizing the system at the point of the current estimate, and then the linear Kalman filter is used to filter this linearized system. It was one of the very first techniques used for nonlinear problems, and it remains the most common technique. \n",
    "\n",
    "The EKF provides significant mathematical challenges to the designer of the filter; this is the most challenging chapter of the book. I do everything I can to avoid the EKF in favor of other techniques that have been developed to filter nonlinear problems. However, the topic is unavoidable; all classic papers and a majority of current papers in the field use the EKF. Even if you do not use the EKF in your own work you will need to be familiar with the topic to be able to read the literature. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linearizing the Kalman Filter\n",
    "\n",
    "The Kalman filter uses linear equations, so it does not work with nonlinear problems. Problems can be nonlinear in two ways. First, the process model might be nonlinear. An object falling through the atmosphere encounters drag which reduces its acceleration. The drag coefficient varies based on the velocity the object. The resulting behavior is nonlinear - it cannot be modeled with linear equations. Second, the measurements could be nonlinear. For example, a radar gives a range and bearing to a target. We use trigonometry, which is nonlinear, to compute the position of the target.\n",
    "\n",
    "For the linear filter we have these equations for the process and measurement models:\n",
    "\n",
    "$$\\begin{aligned}\\dot{\\mathbf x} &= \\mathbf{Ax} + w_x\\\\\n",
    "\\mathbf z &= \\mathbf{Hx} + w_z\n",
    "\\end{aligned}$$\n",
    "\n",
    "Where $\\mathbf A$ is the systems dynamic matrix. Using the state space methods covered in the **Kalman Filter Math** chapter these equations can be tranformed into \n",
    "$$\\begin{aligned}\\bar{\\mathbf x} &= \\mathbf{Fx} \\\\\n",
    "\\mathbf z &= \\mathbf{Hx}\n",
    "\\end{aligned}$$\n",
    "\n",
    "where $\\mathbf F$ is the *fundamental matrix*. The noise $w_x$ and $w_z$ terms are incorporated into the matrices $\\mathbf R$ and $\\mathbf Q$. This form of the equations allow us to compute the state at step $k$ given a measurement at step $k$ and the state estimate at step $k-1$. In earlier chapters I built your intuition and minimized the math by using problems describable with Newton's equations. We know how to design $\\mathbf F$ based on high school physics.\n",
    "\n",
    "\n",
    "For the nonlinear model the linear expression $\\mathbf{Fx} + \\mathbf{Bu}$ is replaced by a nonlinear function $f(\\mathbf x, \\mathbf u)$, and the linear expression $\\mathbf{Hx}$ is replaced by a nonlinear function $h(\\mathbf x)$:\n",
    "\n",
    "$$\\begin{aligned}\\dot{\\mathbf x} &= f(\\mathbf x, \\mathbf u) + w_x\\\\\n",
    "\\mathbf z &= h(\\mathbf x) + w_z\n",
    "\\end{aligned}$$\n",
    "\n",
    "You might imagine that we could proceed by finding a new set of Kalman filter equations that optimally solve these equations. But if you remember the charts in the **Nonlinear Filtering** chapter you'll recall that passing a Gaussian through a nonlinear function results in a probability distribution that is no longer Gaussian. So this will not work.\n",
    "\n",
    "The EKF does not alter the Kalman filter's linear equations. Instead, it *linearizes* the nonlinear equations at the point of the current estimate, and uses this linearization in the linear Kalman filter. \n",
    "\n",
    "*Linearize* means what it sounds like. We find a line that most closely matches the curve at a defined point. The graph below linearizes the parabola $f(x)=x^2−2x$ at $x=1.5$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import kf_book.ekf_internal as ekf_internal\n",
    "ekf_internal.show_linearization()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the curve above is the process model, then the dotted lines shows the linearization of that curve for the estimate $x=1.5$.\n",
    "\n",
    "We linearize systems by taking the derivative, which finds the slope of a curve:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "f(x) &= x^2 -2x \\\\\n",
    "\\frac{df}{dx} &= 2x - 2\n",
    "\\end{aligned}$$\n",
    "\n",
    "and then evaluating it at $x$:\n",
    "\n",
    "$$\\begin{aligned}m &= f'(x=1.5) \\\\&= 2(1.5) - 2 \\\\&= 1\\end{aligned}$$ \n",
    "\n",
    "Linearizing systems of differential equations is similar. We linearize $f(\\mathbf x, \\mathbf u)$, and $h(\\mathbf x)$ by taking the partial derivatives of each to evaluate $\\mathbf F$ and $\\mathbf H$ at the point $\\mathbf x_t$ and $\\mathbf u_t$. We call the partial derivative of a matrix the [*Jacobian*](https://en.wikipedia.org/wiki/Jacobian_matrix_and_determinant). This gives us the the discrete state transition matrix and measurement model matrix:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\mathbf F \n",
    "&= {\\frac{\\partial{f(\\mathbf x_t, \\mathbf u_t)}}{\\partial{\\mathbf x}}}\\biggr|_{{\\mathbf x_t},{\\mathbf u_t}} \\\\\n",
    "\\mathbf H &= \\frac{\\partial{h(\\bar{\\mathbf x}_t)}}{\\partial{\\bar{\\mathbf x}}}\\biggr|_{\\bar{\\mathbf x}_t} \n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "This leads to the following equations for the EKF. I put boxes around the differences from the linear filter:\n",
    "\n",
    "$$\\begin{array}{l|l}\n",
    "\\text{linear Kalman filter} & \\text{EKF} \\\\\n",
    "\\hline \n",
    "& \\boxed{\\mathbf F = {\\frac{\\partial{f(\\mathbf x_t, \\mathbf u_t)}}{\\partial{\\mathbf x}}}\\biggr|_{{\\mathbf x_t},{\\mathbf u_t}}} \\\\\n",
    "\\mathbf{\\bar x} = \\mathbf{Fx} + \\mathbf{Bu} & \\boxed{\\mathbf{\\bar x} = f(\\mathbf x, \\mathbf u)}  \\\\\n",
    "\\mathbf{\\bar P} = \\mathbf{FPF}^\\mathsf{T}+\\mathbf Q  & \\mathbf{\\bar P} = \\mathbf{FPF}^\\mathsf{T}+\\mathbf Q \\\\\n",
    "\\hline\n",
    "& \\boxed{\\mathbf H = \\frac{\\partial{h(\\bar{\\mathbf x}_t)}}{\\partial{\\bar{\\mathbf x}}}\\biggr|_{\\bar{\\mathbf x}_t}} \\\\\n",
    "\\textbf{y} = \\mathbf z - \\mathbf{H \\bar{x}} & \\textbf{y} = \\mathbf z - \\boxed{h(\\bar{x})}\\\\\n",
    "\\mathbf{K} = \\mathbf{\\bar{P}H}^\\mathsf{T} (\\mathbf{H\\bar{P}H}^\\mathsf{T} + \\mathbf R)^{-1} & \\mathbf{K} = \\mathbf{\\bar{P}H}^\\mathsf{T} (\\mathbf{H\\bar{P}H}^\\mathsf{T} + \\mathbf R)^{-1} \\\\\n",
    "\\mathbf x=\\mathbf{\\bar{x}} +\\mathbf{K\\textbf{y}} & \\mathbf x=\\mathbf{\\bar{x}} +\\mathbf{K\\textbf{y}} \\\\\n",
    "\\mathbf P= (\\mathbf{I}-\\mathbf{KH})\\mathbf{\\bar{P}} & \\mathbf P= (\\mathbf{I}-\\mathbf{KH})\\mathbf{\\bar{P}}\n",
    "\\end{array}$$\n",
    "\n",
    "We don't normally use $\\mathbf{Fx}$ to propagate the state for the EKF as the linearization causes inaccuracies. It is typical to compute $\\bar{\\mathbf x}$ using a suitable numerical integration technique such as Euler or Runge Kutta. Thus I wrote $\\mathbf{\\bar x} = f(\\mathbf x, \\mathbf u)$. For the same reasons we don't use $\\mathbf{H\\bar{x}}$ in the computation for the residual, opting for the more accurate $h(\\bar{\\mathbf x})$.\n",
    "\n",
    "I think the easiest way to understand the EKF is to start off with an example. Later you may want to come back and reread this section."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Tracking a Airplane\n",
    "\n",
    "This example tracks an airplane using ground based radar. We implemented a UKF for this problem in the last chapter. Now we will implement an EKF for the same problem so we can compare both the filter performance and the level of effort required to implement the filter.\n",
    "\n",
    "Radars work by emitting a beam of radio waves and scanning for a return bounce. Anything in the beam's path will reflects some of the signal back to the radar. By timing how long it takes for the reflected signal to get back to the radar the system can compute the *slant distance* - the straight line distance from the radar installation to the object.\n",
    "\n",
    "The relationship between the radar's slant range distance $r$ and elevation angle $\\epsilon$ with the horizontal position $x$ and altitude $y$ of the aircraft is illustrated in the figure below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ekf_internal.show_radar_chart()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This gives us the equalities:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\epsilon &= \\tan^{-1} \\frac y x\\\\\n",
    "r^2 &= x^2 + y^2\n",
    "\\end{aligned}$$ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the State Variables\n",
    "\n",
    "We want to track the position of an aircraft assuming a constant velocity and altitude, and measurements of the slant distance to the aircraft. That means we need 3 state variables - horizontal distance, horizonal velocity, and altitude:\n",
    "\n",
    "$$\\mathbf x = \\begin{bmatrix}\\mathtt{distance} \\\\\\mathtt{velocity}\\\\ \\mathtt{altitude}\\end{bmatrix}=    \\begin{bmatrix}x \\\\ \\dot x\\\\ y\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Process Model\n",
    "\n",
    "We assume a Newtonian, kinematic system for the aircraft. We've used this model in previous chapters, so by inspection you may recognize that we want\n",
    "\n",
    "$$\\mathbf F = \\left[\\begin{array}{cc|c} 1 & \\Delta t & 0\\\\\n",
    "0 & 1 & 0 \\\\ \\hline\n",
    "0 & 0 & 1\\end{array}\\right]$$\n",
    "\n",
    "I've partioned the matrix into blocks to show the upper left block is a constant velocity model for $x$, and the lower right block is a constant position model for $y$.\n",
    "\n",
    "However, let's practice finding these matrices. We model systems with a set of differential equations. We need an equation in the form \n",
    "\n",
    "$$\\dot{\\mathbf x} = \\mathbf{Ax} + \\mathbf{w}$$\n",
    "where $\\mathbf{w}$ is the system noise. \n",
    "\n",
    "The variables $x$ and $y$ are independent so we can compute them separately. The differential equations for motion in one dimension are:\n",
    "\n",
    "$$\\begin{aligned}v &= \\dot x \\\\\n",
    "a &= \\ddot{x} = 0\\end{aligned}$$\n",
    "\n",
    "Now we put the differential equations into state-space form. If this was a second or greater order differential system we would have to first reduce them to an equivalent set of first degree equations. The equations are first order, so we put them in state space matrix form as\n",
    "\n",
    "$$\\begin{aligned}\\begin{bmatrix}\\dot x \\\\ \\ddot{x}\\end{bmatrix} &= \\begin{bmatrix}0&1\\\\0&0\\end{bmatrix} \\begin{bmatrix}x \\\\ \n",
    "\\dot x\\end{bmatrix} \\\\ \\dot{\\mathbf x} &= \\mathbf{Ax}\\end{aligned}$$\n",
    "where $\\mathbf A=\\begin{bmatrix}0&1\\\\0&0\\end{bmatrix}$. \n",
    "\n",
    "Recall that $\\mathbf A$ is the *system dynamics matrix*. It describes a set of linear differential equations. From it we must compute the state transition matrix $\\mathbf F$. $\\mathbf F$ describes a discrete set of linear equations which compute $\\mathbf x$ for a discrete time step $\\Delta t$.\n",
    "\n",
    "A common way to compute $\\mathbf F$ is to use the power series expansion of the matrix exponential:\n",
    "\n",
    "$$\\mathbf F(\\Delta t) = e^{\\mathbf A\\Delta t} = \\mathbf{I} + \\mathbf A\\Delta t  + \\frac{(\\mathbf A\\Delta t)^2}{2!} + \\frac{(\\mathbf A \\Delta t)^3}{3!} + ... $$\n",
    "\n",
    "\n",
    "$\\mathbf A^2 = \\begin{bmatrix}0&0\\\\0&0\\end{bmatrix}$, so all higher powers of $\\mathbf A$ are also $\\mathbf{0}$. Thus the power series expansion is:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\mathbf F &=\\mathbf{I} + \\mathbf At + \\mathbf{0} \\\\\n",
    "&= \\begin{bmatrix}1&0\\\\0&1\\end{bmatrix} + \\begin{bmatrix}0&1\\\\0&0\\end{bmatrix}\\Delta t\\\\\n",
    "\\mathbf F &= \\begin{bmatrix}1&\\Delta t\\\\0&1\\end{bmatrix}\n",
    "\\end{aligned}$$\n",
    "\n",
    "This is the same result used by the kinematic equations! This exercise was unnecessary other than to illustrate finding the state transition matrix from linear differential equations. We will conclude the chapter with an example that will require the use of this technique."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Measurement Model\n",
    "\n",
    "The measurement function takes the state estimate of the prior $\\bar{\\mathbf x}$ and turn it into a measurement of the slant range distance. We use the Pythagorean theorem to derive:\n",
    "\n",
    "$$h(\\bar{\\mathbf x}) = \\sqrt{x^2 + y^2}$$\n",
    "\n",
    "The relationship between the slant distance and the position on the ground is nonlinear due to the square root. We linearize it by evaluating its partial derivative at $\\mathbf x_t$:\n",
    "\n",
    "$$\n",
    "\\mathbf H = \\frac{\\partial{h(\\bar{\\mathbf x})}}{\\partial{\\bar{\\mathbf x}}}\\biggr|_{\\bar{\\mathbf x}_t}\n",
    "$$\n",
    "\n",
    "The partial derivative of a matrix is called a Jacobian, and takes the form \n",
    "\n",
    "$$\\frac{\\partial \\mathbf H}{\\partial \\bar{\\mathbf x}} = \n",
    "\\begin{bmatrix}\n",
    "\\frac{\\partial h_1}{\\partial x_1} & \\frac{\\partial h_1}{\\partial x_2} &\\dots \\\\\n",
    "\\frac{\\partial h_2}{\\partial x_1} & \\frac{\\partial h_2}{\\partial x_2} &\\dots \\\\\n",
    "\\vdots & \\vdots\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "In other words, each element in the matrix is the partial derivative of the function $h$ with respect to the $x$ variables. For our problem we have\n",
    "\n",
    "$$\\mathbf H = \\begin{bmatrix}{\\partial h}/{\\partial x} & {\\partial h}/{\\partial \\dot{x}} & {\\partial h}/{\\partial y}\\end{bmatrix}$$\n",
    "\n",
    "Solving each in turn:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\frac{\\partial h}{\\partial x} &= \\frac{\\partial}{\\partial x} \\sqrt{x^2 + y^2} \\\\\n",
    "&= \\frac{x}{\\sqrt{x^2 + y^2}}\n",
    "\\end{aligned}$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\frac{\\partial h}{\\partial \\dot{x}} &=\n",
    "\\frac{\\partial}{\\partial \\dot{x}} \\sqrt{x^2 + y^2} \\\\ \n",
    "&= 0\n",
    "\\end{aligned}$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\frac{\\partial h}{\\partial y} &= \\frac{\\partial}{\\partial y} \\sqrt{x^2 + y^2} \\\\ \n",
    "&= \\frac{y}{\\sqrt{x^2 + y^2}}\n",
    "\\end{aligned}$$\n",
    "\n",
    "giving us \n",
    "\n",
    "$$\\mathbf H = \n",
    "\\begin{bmatrix}\n",
    "\\frac{x}{\\sqrt{x^2 + y^2}} & \n",
    "0 &\n",
    "&\n",
    "\\frac{y}{\\sqrt{x^2 + y^2}}\n",
    "\\end{bmatrix}$$\n",
    "\n",
    "This may seem daunting, so step back and recognize that all of this math is doing something very simple. We have an equation for the slant range to the airplane which is nonlinear. The Kalman filter only works with linear equations, so we need to find a linear equation that approximates $\\mathbf H$. As we discussed above, finding the slope of a nonlinear equation at a given point is a good approximation. For the Kalman filter, the 'given point' is the state variable $\\mathbf x$ so we need to take the derivative of the slant range with respect to $\\mathbf x$. For the linear Kalman filter $\\mathbf H$ was a constant that we computed prior to running the filter. For the EKF $\\mathbf H$ is updated at each step as the evaluation point $\\bar{\\mathbf x}$ changes at each epoch.\n",
    "\n",
    "To make this more concrete, let's now write a Python function that computes the Jacobian of $h$ for this problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sqrt\n",
    "def HJacobian_at(x):\n",
    "    \"\"\" compute Jacobian of H matrix at x \"\"\"\n",
    "\n",
    "    horiz_dist = x[0]\n",
    "    altitude   = x[2]\n",
    "    denom = sqrt(horiz_dist**2 + altitude**2)\n",
    "    return array ([[horiz_dist/denom, 0., altitude/denom]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, let's provide the code for $h(\\bar{\\mathbf x})$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hx(x):\n",
    "    \"\"\" compute measurement for slant range that\n",
    "    would correspond to state x.\n",
    "    \"\"\"\n",
    "    \n",
    "    return (x[0]**2 + x[2]**2) ** 0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's write a simulation for our radar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy.random import randn\n",
    "import math\n",
    "\n",
    "class RadarSim(object):\n",
    "    \"\"\" Simulates the radar signal returns from an object\n",
    "    flying at a constant altityude and velocity in 1D. \n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, dt, pos, vel, alt):\n",
    "        self.pos = pos\n",
    "        self.vel = vel\n",
    "        self.alt = alt\n",
    "        self.dt = dt\n",
    "        \n",
    "    def get_range(self):\n",
    "        \"\"\" Returns slant range to the object. Call once \n",
    "        for each new measurement at dt time from last call.\n",
    "        \"\"\"\n",
    "        \n",
    "        # add some process noise to the system\n",
    "        self.vel = self.vel  + .1*randn()\n",
    "        self.alt = self.alt + .1*randn()\n",
    "        self.pos = self.pos + self.vel*self.dt\n",
    "    \n",
    "        # add measurement noise\n",
    "        err = self.pos * 0.05*randn()\n",
    "        slant_dist = math.sqrt(self.pos**2 + self.alt**2)\n",
    "        \n",
    "        return slant_dist + err"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design Process and Measurement Noise\n",
    "\n",
    "The radar measures the range to a target. We will use $\\sigma_{range}= 5$ meters for the noise. This gives us\n",
    "\n",
    "$$\\mathbf R = \\begin{bmatrix}\\sigma_{range}^2\\end{bmatrix} = \\begin{bmatrix}25\\end{bmatrix}$$\n",
    "\n",
    "\n",
    "The design of $\\mathbf Q$ requires some discussion. The state $\\mathbf x= \\begin{bmatrix}x & \\dot x & y\\end{bmatrix}^\\mathtt{T}$. The first two elements are position (down range distance) and velocity, so we can use `Q_discrete_white_noise` noise to compute the values for the upper left hand side of $\\mathbf Q$. The third element of  $\\mathbf x$ is altitude, which we are assuming is independent of the down range distance. That leads us to a block design of $\\mathbf Q$ of:\n",
    "\n",
    "$$\\mathbf Q = \\begin{bmatrix}\\mathbf Q_\\mathtt{x} & 0 \\\\ 0 & \\mathbf Q_\\mathtt{y}\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Implementation\n",
    "\n",
    "`FilterPy` provides the class `ExtendedKalmanFilter`. It works similarly to the `KalmanFilter` class we have been using, except that it allows you to provide a function that computes the Jacobian of $\\mathbf H$ and the function $h(\\mathbf x)$. \n",
    "\n",
    "We start by importing the filter and creating it. The dimension of `x` is 3 and `z` has dimension 1.\n",
    "\n",
    "```python\n",
    "from filterpy.kalman import ExtendedKalmanFilter\n",
    "\n",
    "rk = ExtendedKalmanFilter(dim_x=3, dim_z=1)\n",
    "```\n",
    "We create the radar simulator:\n",
    "```python\n",
    "radar = RadarSim(dt, pos=0., vel=100., alt=1000.)\n",
    "```\n",
    "We will initialize the filter near the airplane's actual position:\n",
    "\n",
    "```python\n",
    "rk.x = array([radar.pos, radar.vel-10, radar.alt+100])\n",
    "```\n",
    "\n",
    "We assign the system matrix using the first term of the Taylor series expansion we computed above:\n",
    "\n",
    "```python\n",
    "dt = 0.05\n",
    "rk.F = eye(3) + array([[0, 1, 0],\n",
    "                       [0, 0, 0],\n",
    "                       [0, 0, 0]])*dt\n",
    "```\n",
    "\n",
    "After assigning reasonable values to $\\mathbf R$, $\\mathbf Q$, and $\\mathbf P$ we can run the filter with a simple loop. We pass the functions for computing the Jacobian of $\\mathbf  H$ and $h(x)$ into the `update` method.\n",
    "\n",
    "```python\n",
    "for i in range(int(20/dt)):\n",
    "    z = radar.get_range()\n",
    "    rk.update(array([z]), HJacobian_at, hx)\n",
    "    rk.predict()\n",
    "```\n",
    "\n",
    "Adding some boilerplate code to save and plot the results we get:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2YAAAGGCAYAAAAQDpJVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xt4VOWdB/DvySSZ3EOuEBJyIUAit6C9ILYoF4nUWkvYtdsqjyVW+rSC0rVuyrUEFGStjxURdgVtwYpblS2w1QJ9hFXbsihtLZBAQsiFkBtJhpB7JnM5+8c4xzmZIcyEeWfmjN/P8/Ag857z8p7vzLzyyznnPZIsyzKIiIiIiIjIb0L8PQAiIiIiIqIvOhZmREREREREfsbCjIiIiIiIyM9YmBEREREREfkZCzMiIiIiIiI/Y2FGRERERETkZyzMiIiIiIiI/IyFGRERERERkZ+xMCMiIiIiIvKzgCjMuru7UVJSgsLCQqSkpECSJJSWlrrc1mQy4YUXXsC0adMQGRmJUaNG4Y477sCJEyecttu4cSOys7Oh1+uRn5+P7du3u+yzpqYGixcvxqhRoxATE4MFCxbg73//u7cPk4iIiIiIyKWAKMwMBgN27doFo9GIRYsWXXc7i8WCoqIibNq0Cd/73vdw+PBh7Nu3DwsXLkRvb69q28ceewzPPvssli9fjqNHj6KoqAgrV67Eli1bVNu1tbVh9uzZuHDhAn71q1/h7bffxsDAAObMmYPKykohx0tERERERORIkmVZ9vcg7EOQJAnt7e1ISUnBhg0bnM6avfjii/jpT3+Kv/zlL7j99tuv2195eTmmTZuGzZs3Y/Xq1crrP/zhD/HGG2+goaEBiYmJAICSkhK8+OKLqKqqQlZWFgCgq6sLubm5mDdvHt566y0vHy0REREREZFaqL8HANgKMnds27YNd95557BFGQAcPHgQsiyjuLhY9XpxcTF2796NI0eO4MEHHwQAHDhwAPPmzVOKMgCIi4vD4sWL8Zvf/AZmsxmhobaYrFYrrFar09jdHT8REREREX0xyLKMoefAQkJCEBLi+qLFgCjM3HH58mXU1dXhW9/6FtasWYPXXnsNBoMBeXl5KCkpwfe//31l27KyMqSkpGDMmDGqPqZPn660A0B/fz+qq6tRVFTk9PdNnz4d/f39qKmpwaRJkwDYCrOhl0wSERERERG5Izo6WvuFWWNjIwBg7969yMjIwMsvv4z4+Hjs3r0bS5cuxeDgIJYtWwbAds+a/VJFR9HR0QgPD4fBYAAAdHR0QJZll9vaX7NvS0REREREJIpmCjP7JYQDAwP4wx/+oFx6uGDBAnz5y1/Gpk2blMIMGP7yyKFtnmxLRERERETkbQGxKqM7kpKSAAD5+fmq+8EkScI999yDhoYGtLa2Ktu6OtPV29uLwcFB5WxYQkICJElyue3Vq1cBwOXZNCIiIiIiIm/SzBmz3NxcREVFuWyz31Rnv15z2rRp+O1vf4uWlhbVfWZnz54FAEydOhUAEBkZiQkTJiivOzp79iwiIyMxfvx45TVXZ8+Gu06UiIiIiIi+mFytTzHc1XiaKcxCQ0Px7W9/G/v370ddXR2ys7MB2IqyI0eOIDc3F8nJyQCAb3/721i3bh327t2Ln/3sZ0ofe/bsQWRkJBYuXKi8VlRUhBdffBGXL1/GuHHjANgeeP273/0O999/v7IiI+A6yOFWViEiIiIiIrIbrjDTlQ59WJifHD58GKdPn8bZs2dx6NAhpKamQpIknDt3DtnZ2QgLC8OMGTOwZ88eHDx4EMnJyaivr8eqVavw4Ycf4pVXXsHkyZMBAKmpqWhoaMC2bdsQEREBk8mE3bt3Y9u2bSgtLUVhYaHy986YMQN79+7FwYMHkZaWhtraWjz22GNoaGjAvn37lGIPsBWBg4ODqnHr9Xreh0ZERERERCqe1g4B8YBpAMjOzsalS5dcttXW1ipnyMrKyrBq1Sp89NFHMJlMmDFjBtauXYv77rtPtY/JZMLmzZvx61//Gi0tLcjOzsaKFSvw+OOPO/VfXV2Np556CsePH4fZbMasWbPw3HPP4bbbblNtZ7Va0d3drXotNjbW72fMLly4oDxvzb60P3kXMxaPGYvHjMVjxr7BnMVjxuIxY/H8nbGntUPAXMpYV1fn1nZTp07Fu+++e8PtwsLCUFpaCndOCObm5uLAgQNu/f2BqL+/HyaTCWFhYf4eStBixuIxY/GYsXjM2DeYs3jMWDxmLJ7WMubNUUFAkiTlF4nBjMVjxuIxY/GYsW8wZ/GYsXjMWDytZRwwlzJqQaBeykhERERERIHF09qBFQUREREREZGfsTAjIiIiIiLyMxZmREREREREfhYwqzLSyLW1tcFisUCn0yElJcXfwwlKzFg8ZiweMxaPGfsGcxaPGYvHjMXTWsYszIJAU1OTshSoFj50WsSMxWPG4jFj8ZixbzBn8ZixeMxYPK1lzEsZiYiIiIiI/IxnzIJAVlYWrFYrl+0XiBmLx4zFY8biMWPfYM7iMWPxmLF4WsuYzzHzAJ9jRkRERERE7uBzzIiIiIiIiDSGhRkREREREZGf8R6zIGA2myHLMiRJQmgo31IRmLF4zFg8ZiweM/YN5iweMxaPGYuntYwDf4R0Q+Xl5cpSoAUFBf4eTlBixuIxY/GYsXjM2DeYs3jMWDxmLJ7WMualjERERERERH7GM2ZBIC4uDmazWROnaLWKGYvHjMVjxuIxY99gzuIxY/GYsXhay5jL5XuAy+UTEREREZE7uFw+ERERERGRxrAwIyIiIiIi8jMWZkRERERERH6mjTvhaFg1NTXKjY3jx4/393CCEjMWjxmLx4zFY8a+wZzFY8biMWPxtJYxC7Mg0N3drTyjgcRgxuIxY/GYsXjM2DeYs3jMWDxmLJ7WMualjERERERERH7G5fI9EKjL5VssFuW/dTqdH0cSvJixeMxYPGYsHjP2DeYsHjMWjxmL5++MPa0deCljEOCXWTxmLB4zFo8Zi8eMfYM5i8eMxWPG4mktY17KSERERERE5GcszIiIiIiIiPyMlzIGgY6ODlitVoSEhCAhIcHfwwlKzFg8ZiweMxaPGfsGcxaPGYvHjMXTWsYszIJAfX29shSoFj50WsSMxWPG4jFj8ZixbzBn8ZixeMxYPK1lzEsZiYiIiIiI/IxnzIJAenq6cpqWxGDG4jFj8ZixeMzYN5izeMxYPGYsntYy5nPMPBCozzEjIiIiIqLA4mntwIqCiIiIiIjIzwKiMOvu7kZJSQkKCwuRkpICSZJQWlrqtN3SpUshSZLTr/z8fKdtTSYTNm7ciOzsbOj1euTn52P79u0u//6amhosXrwYo0aNQkxMDBYsWIC///3v3j5MIiIiIiIilwLiHjODwYBdu3ahoKAAixYtwquvvnrdbSMjI3H8+HGn14Z67LHH8Jvf/AZPP/00vvKVr+Do0aNYuXIluru7sWbNGmW7trY2zJ49GwkJCfjVr36FiIgIPPvss5gzZw5OnTqFvLw87x0oERERERGRCwFRmGVlZaGjowOSJKG9vX3YwiwkJAS33377sP2Vl5fjtddew+bNm/Fv//ZvAIA5c+bAYDDgmWeewY9+9CMkJiYCAH7xi1+gra0NJ06cQFZWFgDg61//OnJzc/Hzn/8cb731lpeOUpzTp08rS4EWFBT4ezhBiRmLx4zFY8biMWPfYM7iMWPxmLF4Wss4IC5ltF+S6C0HDx6ELMsoLi5WvV5cXIz+/n4cOXJEee3AgQOYN2+eUpQBQFxcHBYvXozf//73MJvNXhsXERERERGRKwFRmHmiv78fY8aMgU6nQ0ZGBlasWIGrV6+qtikrK0NKSgrGjBmjen369OlKu72v6upq5fWh2/b396OmpkbQkXhPVFQUoqOjERUV5e+hBC1mLB4zFo8Zi8eMfYM5i8eMxWPG4mkt44C4lNFdBQUFKCgowNSpUwEAH374IX75y1/i2LFjOHXqFGJiYgDY7lmzX6roKDo6GuHh4TAYDACAjo4OyLLsclv7a/Ztr6e8vBxZWVmIi4tTXjMajaioqAAAJCQkIDMzU7VPVVUV+vr6lGNy1N7ejsbGRgBAZmam6inlFotFKSpjY2Mxfvx4AMDEiRMBALW1tTh9+jQAYMqUKQgN/fztvXbtGi5dugQAGDt2LFJSUlR/75kzZyDLMiIjIzFp0iRV2+XLl5XiNy8vDxEREUpbT08PqqurAQCpqalIS0tT7Xvu3DnlFPLkyZNVbc3NzWhtbQUA5ObmKu8fAAwMDKCyshKA7b0YN26cat8LFy6gv78fkiQ5FdZtbW1oamoCYLtMdtSoUUqb2WxGeXk5ANuZ0ZycHNW+NTU1yrKmU6dOhU6nA2DLuKOjA/X19Th9+jTS09ORnJys2teefVRUlPKe2NXX16OjowMAkJ+fD71er7R1dXWhtrYWADB69GinHyiUl5fDbDYri9g4ampqQltbGwBgwoQJiI6OVtr6+vpQVVUFAEhKSkJGRoZq38rKSgwMDECn0ynfKbvW1lY0NzcDALKzsxEfH6+0DQ4O4vz58wCA+Ph4ZGdnq/atrq5GT08PAGDatGmqJWENBgMaGhoAABkZGUhKSlLacnNzcfbsWQwODqK6uhq5ubmqfuvq6tDZ2QkAuOWWWxAeHq60dXZ2oq6uDgCQlpaG1NRU1b5lZWWwWCyIiIhwum+0oaFB+Z5PnDhRNXn39vbi4sWLAICUlBSMHTtWtW9FRQWMRiNCQ0MxZcoUVVtLSwuuXLkCAMjJyfHrHGEXGhqKvr4+DA4Owmw2c46A9+YIwPb/FPv7NjQ/gHOE3UjnCKvVirNnzwIAYmJicMstt6j65RxhczNzRG1tLbq6ugDw3xGi5oj6+noAtudrDZ0HOEfYeGuOyM3NVeXojznC/j11l6YKs3/9139V/XnBggW49dZb8c///M/YvXu3qn24SyOHtnmy7VBmsxlDHwUnyzJMJpPS7mofe/tQVqtVabNarU7t7vY7dEyO/VosFpf9yrKMsLAwpzaLxXJT/V7vWB37HXqsjhm66td+rK7eH3f7DZT35kbHajKZYDabXT7zYrj3xp1+TSaTy7bh+rXve6N+XXE3Q1f7O45pqBsd6+DgIKxWq+p/kK76HWmGrjJyt99A+RxyjnDuN1DeG84Rzv1yjuAcMbRfzhGcIxz7DaQ5whOaKsxcKSoqQnR0NE6ePKm8lpSUhH/84x9O2/b29mJwcFA5G5aQkABJklyeFbP/ZMfV2TRHoaGhLgs9+8Tk+NMmx31cTVyAbXETe5urL5C7/Q4dk2O/rj5UYWFhkGXZZb86ne6m+nX8/Xr9Dj1Wxwxd9Ws/VlcTqrv9Bsp7c6NjtR/njTIcSb8Wi8Vl23D92vcdrt+bzfBGxzrUjY41PDwcFotFSIZWq9Xj700gfg45Rzj3GyjvDecI5345R3COGNov5wjOEY79BtIc4QlJ9rSUE6y9vR0pKSnYsGGDy2eZDWW1WhEbG4v7778f//Vf/wUA2LJlC9auXYvm5mbV6dyTJ09i1qxZ2LdvHx588EEAwKRJk5Cbm4vDhw+r+v3Rj36E119/HV1dXcoXxNOndxMRERER0ReTp7WD5iuK/fv3o6+vT7WE/re//W1IkoS9e/eqtt2zZw8iIyOxcOFC5bWioiIcP34cly9fVl7r7u7G7373O9x///0uf2oRaOrr61FTU6Nct0zex4zFY8biMWPxmLFvMGfxmLF4zFg8rWUcMFXH4cOH0dvbq1SV586dw/79+wEA9957L9ra2vDggw/iu9/9LiZMmABJkvDhhx/ixRdfxJQpU/Doo48qfU2ZMgU/+MEPsGHDBuh0OnzlK1/BH//4R+zatQvPPPOM6vLEp556Cr/5zW/wzW9+E5s2bYJer8fWrVsxMDDg1hm7QNDR0aHcGDv0BmHyDmYsHjMWjxmLx4x9gzmLx4zFY8biaS3jgCnMfvzjHyur/QDAO++8g3feeQeAbZWg+Ph4jB49Gi+88AKuXLkCi8WCrKwsPPHEE1izZo1qFRkA2LlzJ9LT07F9+3a0tLQgOzsb27Ztw+OPP67aLiUlBX/605/w1FNP4fvf/z7MZjNmzZqFDz74wGnlGiIiIiIiIhEC7h6zQBao95gZjUbIsgxJklTLp5L3MGPxmLF4zFg8ZuwbzFk8ZiweMxbP3xl7WjuwMPNAoBZmREREREQUWL5wi38QERERERFpHQszIiIiIiIiPwuYxT9o5Lq6upTrZ+Pi4vw9nKDEjMVjxuIxY/GYsW8wZ/GYsXjMWDytZczCLAjU1tYqS4EWFBT4ezhBiRmLx4zFY8biMWPfYM7iMWPxmLF4WsuYlzISERERERH5Gc+YBYHRo0fDYrFAp9P5eyhBixmLx4zFY8biMWPfYM7iMWPxmLF4WsuYy+V7gMvlExERERGRO7hcPhERERERkcawMCMiIiIiIvIzFmZERERERER+xsU/gkB5ebmyFOiUKVP8PZygxIzFY8biMWPxmLFvMGfxmLF4zFg8rWXMwiwImM1mmM1mSJLk76EELWYsHjMWjxmLx4x9gzmLx4zFY8biaS1jFmZBQK/XIyQkBGFhYf4eStBixuIxY/GYsXjM2DeYs3jMWDxmLJ7WMuZy+R7gcvlEREREROQOLpdPRERERESkMSzMiIiIiIiI/IyFGRERERERkZ9x8Y8g0NTUBIvFAp1Oh7Fjx/p7OEGJGYvHjMVjxuIxY99gzuIxY/GYsXhay5iFWRBoa2tTntGghQ+dFjFj8ZixeMxYPGbsG8xZPGYsHjMWT2sZ81JGIiIiIiIiP+Ny+R4I1OXye3t7IcsyJElCdHS0X8cSrJixeMxYPGYsHjP2DeYsHjMWjxmL5++MPa0dWJh5IFALMyIiIiIiCix8jhkREREREZHGsDAjIiIiIiLyM67KGAT6+vqU62ejoqL8PZygxIzFY8biMWPxmLFvMGfxmLF4zFg8rWXMwiwIVFVVKUuBFhQU+Hs4QYkZi8eMxWPG4jFj32DO4jFj8ZixeFrLmJcyEhERERER+RnPmAWBpKQk5anmJAYzFo8Zi8eMxWPGvsGcxWPG4jFj8bSWMZfL9wCXyyciIiIiIndwuXwiIiIiIiKNYWFGRERERETkZyzMiIiIiIiI/IyLfwSByspKZSnQvLw8fw8nKDFj8ZixeMxYPGbsG8xZPGYsHjMWT2sZ+/2MWXd3N0pKSlBYWIiUlBRIkoTS0tJh95FlGXfeeSckScKKFStcbrN9+3bk5+dDr9cjJycHGzduhMlkctqutbUVS5cuRXJyMqKiojBr1iwcO3bMG4fmMwMDA8ovEoMZi8eMxWPG4jFj32DO4jFj8ZixeFrL2O+FmcFgwK5du2A0GrFo0SK39tmxYwcuXrx43fbNmzdj5cqVWLx4MY4ePYrHHnsMW7ZswfLly1XbGY1GzJ8/H8eOHcO2bdtw6NAhjB49GgsXLsSHH354U8flSzqdDiEhIZpZClSLmLF4zFg8ZiweM/YN5iweMxaPGYuntYz9vly+/a+XJAnt7e1ISUnBhg0brnvWrK6uDtOmTcPrr7+OxYsXY/ny5Xj55ZeVdoPBgIyMDDz88MN45ZVXlNe3bNmCdevWoaysDJMnTwYA7Ny5E8uXL8eJEycwa9YsAIDZbEZBQQFiYmLw8ccfq/5uLpdPRERERETu0Nxy+ZIkQZIkt7f/4Q9/iAULFqCoqMhl+5EjRzAwMIDi4mLV68XFxZBlGQcPHlReO3DgAPLy8pSiDABCQ0OxZMkSfPLJJ2hsbPTwaIiIiIiIiDynqcU/Xn31VXzyySc4d+7cdbcpKysDAEybNk31elpaGpKTk5V2+7azZ8926mP69OkAgPLycqSnpw87pvLycmRlZSEuLk55zWg0oqKiAgCQkJCAzMxM1T5VVVXo6+sDABQUFKja2tvblYIwMzMTCQkJSpvFYlHGHxsbi/Hjx6v2ra2tRVdXFwBgypQpCA39/O29du0aLl26BAAYO3YsUlJSVPueOXMGsiwjMjISkyZNUrVdvnwZV69eBQDk5eUhIiJCaevp6UF1dTUAIDU1FWlpaap9z507p9x0aT9Tadfc3IzW1lYAQG5uLmJiYpS2gYEBVFZWAgASExMxbtw41b4XLlxAf38/JElS3i+7trY2NDU1AQCysrIwatQopc1sNqO8vBwAEBcXh5ycHNW+NTU1yk82pk6dqjr13dHRgfr6egBAeno6kpOTVfuePn0aABAVFYWJEyeq2urr69HR0QEAyr2Pdl1dXaitrQUAjB49GmPGjFHtW15eDrPZDL1ej/z8fFVbU1MT2traAAATJkxAdHS00tbX14eqqioAtiffZ2RkqPatrKzEwMAAdDodpk6dqmprbW1Fc3MzACA7Oxvx8fFK2+DgIM6fPw8AiI+PR3Z2tmrf6upq9PT0ALB9Dx1/KmQwGNDQ0AAAyMjIQFJSktJmtVpx9uxZAEBMTAxyc3NV/dbV1aGzsxMAcMsttyA8PFxp6+zsRF1dHQDbdz01NVW1b1lZGSwWCyIiIpxu/m1oaIDBYAAATJw4EVFRUUpbb2+vctl0SkoKxo4dq9q3oqICRqMRoaGhmDJliqqtpaUFV65cAQDk5ORwjgDnCM4RNpwjbDhH2HCO+BznCJtgmiPs31N3aaYwa2xsxFNPPYXnnnvOaeJzZDAYoNfrVR8su8TERCU4+7aJiYkut7O334jZbMbQq0FlWVYWGjGbzS73cbUQCWD7UNnbrFarU7u7/Q4dk2O/FovFZb+yLCMsLMypzWKx3FS/1ztWx36HHqtjhq76tR+rq7Ot7vYbKO/NjY7VZDLBbDa7PO093HvjTr8mk8ll23D92ve9Ub+uuJuhq/0dxzTUjY51cHAQVqvV5TXm3sjQVUbu9hson0POEc79Bsp7wznCuV/OEZwjhvbLOYJzhGO/gTRHeEIzhdmPfvQjFBQUYNmyZTfcdrhLI4e2ebKtK6GhoS77tE9Mjj9tctzH1cQFACEhIUqbqy+Qq35bW1thsVhgNpuV9qFjcuzX1YcqLCwMsiy7HK9Op7upfh1/v16/Q4/VMUNX/dozdPUeuduvJ+9Na2srenp6lJtI3X1vXPU73Oflehk6bnO9Yx1JvxaLxWXbcP3a9x2u35F8vtva2hASEuLWsQ51o2MNDw+HxWIRkqHVavX4e+PrOcLO/j9mV5eQc45w7nck741Op4Msy+jp6XH6iSvniM/bbvbzbbFY0NzcDJ1Op+TMOcLmZuYIx37b29uVcaampnKOcNHvzb439n+/2TPmHPF5281+vu2/O2bsrznCE35f/MPR9Rb/2L9/P773ve/hz3/+s+r0YUJCApYtW4bnnnsO0dHRCAsLw+rVq7F161b09vaqTiUCtssMFixYgDfffBOA7VTl7Nmz8fbbb6u2e++993Dffffh6NGjKCwsVF4P1MU/Tp8+rZzmH3pJA3kHMxaPGYvHjMVjxr7BnMVjxuIxY/H8nbHmFv9wR1lZGcxmM26//XYkJCQovwBg9+7dSEhIwHvvvQfg83vL7NeY2rW0tKC9vV11Dey0adOctnPcd+j1skRERERERCJo4lLGpUuXYs6cOU6vz507F4sWLcLKlSuVImrhwoWIiIjAnj17MHPmTGXbPXv2QJIk1bPSioqK8Nhjj+Hjjz9WtjWbzXjjjTcwc+bMYe9lCyTZ2dmQZdnj06XkPmYsHjMWjxmLx4x9gzmLx4zFY8biaS3jgCjMDh8+jN7eXuVU37lz57B//34AwL333ovs7GynFVvs0tPTVUVbYmIi1q1bh/Xr1yMxMRGFhYU4deoUSktL8eijj6pW9HnkkUewY8cOPPDAA9i6dStSU1Oxc+dOVFZW4v333xd2vN7muNINicGMxWPG4jFj8ZixbzBn8ZixeMxYPK1lHBD3mGVnZytLsA5VW1t73aJMkiSnB0zbvfTSS9ixYwfq6uowZswYFBcXY+3atU437V25cgUlJSV499130dfXhxkzZuDpp5/G3Xff7dRnoN5jRkREREREgcXT2iEgCjOtYGFGRERERETu8LR2CIhLGenmDA4OKv/t+LA88h5mLB4zFo8Zi8eMfYM5i8eMxWPG4mktYxZmQeD8+fNcblUwZiweMxaPGYvHjH2DOYvHjMVjxuJpLWNeg0dERERERORnPGMWBOLj46/75HXyDmYsHjMWjxmLx4x9gzmLx4zFY8biaS1jLv7hAS7+QURERERE7vC0dmBFQURERERE5GcszIiIiIiIiPyMhRkREREREZGfcfGPIFBdXa0sBZqbm+vv4QQlZiweMxaPGYvHjH2DOYvHjMVjxuJpLWMWZkGgp6dH+dCRGMxYPGYsHjMWjxn7BnMWjxmLx4zF01rGvJSRiIiIiIjIz7hcvgcCdbl8q9Wq/Le/xxKsmLF4zFg8ZiweM/YN5iweMxaPGYvn74w9rR14KWMQ4JdZPGYsHjMWjxmLx4x9gzmLx4zFY8biaS1jbY2WiIiIiIgoCI34jFl/fz9aWlrQ39+P5ORkpKamenNcREREREREXxgeFWaNjY3YvXs33nvvPfzjH/9QXbeZlJSEu+66C0uWLMG3vvUtzZ061DKDwQCr1YqQkBAkJSX5ezhBiRmLx4zFY8biMWPfYM7iMWPxmLF4WsvYrcKsubkZa9aswb59+xAdHY077rgDq1atQmpqKiIiInD16lXU1NTg5MmTKCoqQlZWFp599ll897vfFT1+AtDQ0KAsBaqFD50WMWPxmLF4zFg8ZuwbzFk8ZiweMxZPaxm7VZhNmjQJX/3qV/Hb3/4W3/rWt4Z9FkBNTQ1+/etfY/ny5WhsbMRPf/pTrw2WiIiIiIgoGLm1XP7x48cxb948jzru7OxEbW0tZsyYMeLBBZpAXS5fa6dptYgZi8eMxWPG4jFj32DO4jFj8ZixeP7O2NPagc8x80CgFmZERERERBRYPK0dWFEQERERERH52YiWy//000/x5ptv4tKlSxgYGFC1SZKEQ4cOeWVwREREREREXwQeF2avv/46iouLERISgtTUVISHh6vaJUny2uDIPY6PLeBllWIwY/GYsXjMWDxm7BvMWTxmLB7FS1yxAAAgAElEQVQzFk9rGXt8j1leXh7y8vKwd+9eJCQkiBpXQArEe8z+t6IV/33iPPISdbgzJxYFBQV+G0swO336tLLcKjMWgxmLx4zFY8a+wZzFY8biMWPx/J2x8HvMGhsb8cQTT3zhirJA9Wl9B9690IPytkF/D4WIiIiIiEbI40sZb731VjQ2NooYC41AeOhntXVIKGJiYvw7mCAWExOj/MSFxGDG4jFj8ZixbzBn8ZixeMxYPK1l7PGljCdPnkRxcTHeeustTJ8+XdS4AlIgXsq4+6MabP7DeRTdmo5f/kvwPDOOiIiIiEjLPK0dPD5jdvvtt2Px4sW49dZbkZaWhsTERFW7JEk4ffq0p93SCNnPmA2arTfYkoiIiIiIApXHhdm///u/49lnn0VKSgqysrKcVmUk37IXZkYWZkREREREmuVxYbZt2zY88sgjeOWVV6DT6USMiTygVwozi59HQkREREREI+VxYdbV1YUHH3yQRVmAsJ8x6+rpRV1dHbKzs/07oCBVV1cHi8UCnU7HjAVhxuIxY/GYsW8wZ/GYsXjMWDytZexxYfb1r38d586dw7x580SMhzwUrrMVZn1GMzo7O/08muDV2dmpqVV9tIgZi8eMxWPGvsGcxWPG4jFj8bSWscfLCW7btg3/+Z//iUOHDmFwkM/O8jd9mO3Mpcnq0eKaREREREQUQDxeLj82NhYmkwkmkwmSJCEqKkrdoSR5dOamu7sbTz/9NP7xj3/g008/RXt7OzZs2IDS0lLVdi+99BLefPNNXLx4Ed3d3Rg9ejTuuOMOrF+/HlOmTHHqd/v27dixYwdqa2sxduxYLF26FGvWrHGqmFtbW1FSUoJ3330XfX19KCgowDPPPIP58+c79RmIy+X/X7UB39t9Erkp0Tj8+B1cjEUQxx9CMGMxmLF4zFg8ZuwbzFk8ZiweMxbP3xkLXy7/n/7pnyBJ0shG54LBYMCuXbtQUFCARYsW4dVXX73udt/4xjdQUFCAhIQE1NTUYOvWrZg5cyb+9re/IS8vT9l28+bNWL9+PVatWoXCwkKcOnUK69atQ2NjI3bt2qVsZzQaMX/+fFy7dg3btm1DamoqduzYgYULF+L999/HXXfd5bXjFEUf9tly+RYrv9QCMVvxmLF4zFg8ZuwbzFk8ZiweMxZPaxl7fMbM2+x/vSRJaG9vR0pKisszZq6cP38ekydPxvr167Fp0yYAtgIuIyMDDz/8MF555RVl2y1btmDdunUoKyvD5MmTAQA7d+7E8uXLceLECcyaNQsAYDabUVBQgJiYGHz88ceqvy8Qz5iVNXbivu1/xug4PT5ec7ffxkFERERERJ/ztHbwX0XxGUmSRnwGLiUlBQAQGvr5ib8jR45gYGAAxcXFqm2Li4shyzIOHjyovHbgwAHk5eUpRZm9ryVLluCTTz5BY2PjiMblS3o+x4yIiIiISPPcupTx7bffxne+8x2POm5qakJtbS2+9rWvjWhg12OxWGA2m1FbW4tVq1YhNTVVVYSVlZUBAKZNm6baLy0tDcnJyUq7fdvZs2c7/R3Tp08HAJSXlyM9PX3Y8ZSXlyMrKwtxcXHKa0ajERUVFQCAhIQEZGZmqvapqqpCX18fAKCgoEDV1t7erhSEmZmZSEhIUB27ffyxsbEYP3489KG2xT+MJgsqKysxMDAAAJgyZYqqYL127RouXboEABg7dqxS1NqdOXMGsiwjMjISkyZNUrVdvnwZV69eBQDk5eUhIiJCaevp6UF1dTUAIDU1FWlpaap9z507p6yGYz9Tadfc3IzW1lYAQG5uLmJiYpS2gYEBVFZWAgASExMxbtw41b4XLlxAf38/JElS3i+7trY2NDU1AQCysrIwatQopc1sNqO8vBwAEBcXh5ycHNW+NTU1yk82pk6dqjwWorOzE93d3Whvb4ckSUhPT0dycrJq39OnTwMAoqKiMHHiRFVbfX09Ojo6AAD5+fnQ6/VKW1dXF2prawEAo0ePxpgxY1T7lpeXw2w2Q6/XIz8/X9XW1NSEtrY2AMCECRMQHR2ttPX19aGqqgoAkJSUhIyMDNW+9s+LTqfD1KlTVW2tra1obm4GAGRnZyM+Pl5pGxwcxPnz5wEA8fHxTsvPVldXo6enB4Dte+j4UyGDwYCGhgYAQEZGBpKSkpS2jo4O1NXVQZIkxMbGIjc3V9VvXV2dcv/qLbfcoro8obOzE3V1dQBs3/XU1FTVvmVlZbBYLIiIiFBd9gwADQ0NMBgMAICJEyeq7pvt7e3FxYsXAdh+EDR27FjVvhUVFTAajQgNDXW617WlpQVXrlwBAOTk5PhtjnBUWVmJvr4+SJKEqVOnco6A9+YIwPYZvnTpEmRZRnJystOYOEfYjHSOsFqtOHv2LABAr9djzJgxkCRJ+bs5R9jczBxRW1uLrq4uAMC4ceMQEhKiZMw5wuZm54j6+noAQHp6OsLCwiDLspIx5wgbb8wRMTExyM3NRWdnp5JxR0eHz+cI+/fUXW4VZsuXL8eWLVuwYsUKfOc731FNHkP97W9/w69+9Svs2bMHv/jFL7xemEVHR8NoNAIAJk2ahA8++ED1ZTMYDNDr9aoPll1iYqISnH3bxMREl9vZ22/EbDZj6NWgsizDZDIp7a72sbcPZbValTar1fks2NB+7c8xGzRb0dPTo4xl6Jgc+7VYnB9GbTKZIMuyy+VELRaLsu9I+r3esTr2O/RYHTN01a89Q1dnW93t15P3pq6uTvW6O+/N9fod7vNyvQzNZrPL097DvTfu9GsymVy2Ddevfd8b9evKcJ/vS5cuKf252t9xTEPd6FgHBwdhtVpdPn/RGxm6ysjdfkXPEY44R3jW70jeG/s+bW1tTv8Q5Byh7tcVTz7fFy9eRFhYmFKYcI6wuZk5wrHf+vp6mM1mJWPOEc793ux7Y/+3hT1jzhHqfl1x9/Nt/90x45iYGL/MEZ5wqzC7ePEiSktLsXLlSqxYsQK33norbrvtNqSmpiIiIgJXr15FdXU1Tp48iebmZkydOhW/+93vcM8993g0GHecOHECg4ODqK6uxi9/+UvMnTsXx44dU/0karhLI4e2ebKtK6GhoS77tE9Mjj+Rdtznes9TCAkJUdpcfYGG9mu/lNEiAxZZhv6z9qFjcuzX1YfK/lMbV+PV6XTKviPp1/H36/U79FgdM3TVrz1DV++Ru/16+t44HpM77831+h3u83K9DB23cTTce+NOv/aHLnrSr33f4fod6ed7aP/XG9NQNzrW8PBwWCwWIRlarVaPvze+nCOuh3OE9+cIx76G+95wjhj5HGFvc/UPV84RNjczRzj2O/QflJwjnPv113vDOeLGGQbSvyM84dHiHx0dHfj1r3+NP/zhDzh58qTq9Nz48eMxZ84cPPTQQ5g7d65Hg7DzdPGP7u5uTJgwAbfffjsOHToEAFi9ejW2bt2K3t5ep6X8U1JSsGDBArz55psAbKcqZ8+ejbffflu13XvvvYf77rsPR48eRWFhofJ6IC7+0Ws0Y8qGowCAjx6/DZnpaTfYg0aitbVVmXyGnt4m72DG4jFj8ZixbzBn8ZixeMxYPH9nLHS5/ISEBDz55JN48sknAdiux+zv70dSUpJfnqgdGxuL/Px8XLhwQXnNfm/Z2bNnMXPmTOX1lpYWtLe3q66BnTZtmnItqiP7a0Ovlw1E9ksZASA+IXmYLelmcMIUjxmLx4zFY8a+wZzFY8biMWPxtJbxTZ3qiY+Px5gxY/xSlAG2M2xnz57FhAkTlNcWLlyIiIgI7NmzR7Xtnj17IEkSFi1apLxWVFSEiooK1bL4ZrMZb7zxBmbOnOl0E28gCg2REPLZWVKj2fmaWCIiIiIiCnweP2BahMOHD6O3t1c51Xfu3Dns378fAHDvvffCZDJhwYIFePDBBzFx4kRERkbiwoUL2LZtG4xGIzZs2KD0lZiYiHXr1mH9+vVITExUHjBdWlqKRx99VLWizyOPPIIdO3bggQcewNatW5GamoqdO3eisrIS77//vm9DGCFJkhAeGoIBk5VL5hMRERERaZTfHzAN2JbRtC/BOlRtbS3S0tKwYsUK/OUvf8Hly5cxMDCAMWPGYM6cOVi9erXT8qkA8NJLL2HHjh2oq6vDmDFjUFxcjLVr1zqd3bty5QpKSkrw7rvvoq+vDzNmzMDTTz+Nu+92flhzIN5jBgDTS4+ia8CM95+8CxNSY268AxERERERCeVp7RAQhZlWBGphdmvpEXQMWPDSN9Nw/+zb/DqWYFVWVobBwUGEh4dr4t5DLWLG4jFj8ZixbzBn8ZixeMxYPH9n7Gnt4N+Kgrwi7LNVPY0m3mMmisVigdVqdflsC/IOZiweMxaPGfsGcxaPGYvHjMXTWsYBcY8Z3RzbyowWSDr/LMLyRRARETHs8y/o5jFj8ZixeMzYN5izeMxYPGYsntYyHvGljJ2dnTh58iTa29tx7733IiEhwdtjCziBeinjwhc/QkVLN37zg69i9sQUv46FiIiIiIh8dCnj008/jbFjx+Ib3/gGHn74YdTW1gIA5s+fj61bt46kS7oJ+s+eZWY0cVVGIiIiIiIt8rgw27lzJzZu3Igf/OAHeO+99+B4wu2+++7De++959UB0o3pQ203mQ1aWJgREREREWmRx/eYvfzyy3jyySfx3HPPOd1IN3HiRFRVVXltcOSe8M/OmA3yOWZERERERJrkcWFWU1ODe+65x2VbbGwsrl27dtODIs9YzYMAgJa2dgDp/h1MkGpoaIDFYoFOp0NGRoa/hxOUmLF4zFg8ZuwbzFk8ZiweMxZPaxl7XJjFx8fjypUrLtvq6uqQmpp604Miz8gWEwCgo6vHzyMJXgaDASaTCWFhYZr4YmsRMxaPGYvHjH2DOYvHjMVjxuJpLWOP7zGbP38+nnvuOfT29iqvSZIEs9mM//iP/7ju2TQSJ+yzd9Fk4bPCiYiIiIi0yOMzZps2bcJXvvIVTJ48GUVFRZAkCS+//DI+/fRT1NfX4+233xYxThpGcsIo4FI/4hKS/D2UoDVx4kTIsgxJkvw9lKDFjMVjxuIxY99gzuIxY/GYsXhay9jjwmzChAn4y1/+gieffBI7d+6ELMt4/fXXMXfuXOzbtw+ZmZkixknDiIqwPTRPlnR+HknwioqK8vcQgh4zFo8Zi8eMfYM5i8eMxWPG4mktY48LMwCYPHkyjhw5AqPRCIPBgISEBERGRnp7bOSmcJ2tIDNyVUYiIiIiIk0aUWFmp9frMXbsWG+NhUZIH8bl8omIiIiItMytwmzTpk1udyhJEtavXz/iAZHnJKsZANA7YPTzSIJXb2+vco1ydHS0v4cTlJixeMxYPGbsG8xZPGYsHjMWT2sZu1WYlZaWqv4sSRJkWXZ6zY6FmW91d3YAANqv8hlyoly8eFFZbrWgoMDfwwlKzFg8ZiweM/YN5iweMxaPGYuntYzdWi7farUqvyorK5GTk4PNmzejtrYW/f39qK2txdNPP42cnBxUVFSIHjMNERZiK4pNVi6XT0RERESkRR7fY7Zy5Uo8/PDDWL16tfJaVlYW1qxZA5PJhCeeeAKHDx/26iBpeAnxsQA6ERIa7u+hBK2UlBTlyfEkBjMWjxmLx4x9gzmLx4zFY8biaS1jjwuzP/3pT/jpT3/qsu1rX/sann/++ZseFHlmdFIigAaEhOn9PZSgxUVuxGPG4jFj8ZixbzBn8ZixeMxYPK1l7NaljI70ej3++te/umz761//ivBwnrXxtfBQrspIRERERKRlHp8xKyoqwsaNGxETE4MHH3wQCQkJ6OjowL59+7Bp0yY89NBDIsZJw7AXZkazxc8jISIiIiKikfC4MHvhhRdQXV2Nxx9/HE888QRCQ0NhNpshyzLuvPNOvPDCCyLGScPQ84wZEREREZGmeVyYxcbG4vjx4zhy5Ag++OADGAwGJCUlYe7cuSgsLFQtm0++caW5EQDQ1dvv55EEr4qKCmW51fz8fH8PJygxY/GYsXjM2DeYs3jMWDxmLJ7WMva4MLNbuHAhFi5c6M2x0EhZbA+YNvKMmTBGoxEmkwlWKzMWhRmLx4zFY8a+wZzFY8biMWPxtJbxiAszChwR4ba30cznmAkTGhoKWZYRGsqvjCjMWDxmLB4z9g3mLB4zFo8Zi6e1jCVZlj3613xISMgNL1e0WIJzEQqr1Yru7m7Va7GxsQgJ8XhxS68619SFe1/6E5Jj9Pjrurv9OhYiIiIiIvK8dvC4fPz5z3/uVJi1tbXhj3/8IywWCx5++GFPu6SbpA+zL/4RnAUxEREREVGw87gwKy0tdfn64OAg7rnnHqSmpt7smMhD4brPCjOLNq6fJSIiIiIiNa9dgxceHo7HH3+cy+X7gf2MmdFshYdXphIRERERUQDw6p1wkZGRaG5u9maX5IZrhnYAgCzbFgAJ0/GRBd7W0tICi8UCnU6HMWPG+Hs4QYkZi8eMxWPGvsGcxWPG4jFj8bSWsdcKs7a2NvziF79AXl6et7okN10ztCn/bTRbEabz72IkwejKlSvKczC08MXWImYsHjMWjxn7BnMWjxmLx4zF01rGHhdmOTk5Tot/GI1GtLa2IiQkBP/zP//jtcGRe0JDPn8/Bs1WQO/HwRARERERkcc8Lszuuusup8IsIiIC2dnZ+Jd/+RdkZ2d7a2zkpgm54xEa0gSzVbYVZuR1OTk5kGX5ho+KoJFjxuIxY/GYsW8wZ/GYsXjMWDytZexxYbZnzx4Bw6CbERcXh/DQEJgHLTByyXwh4uLi/D2EoMeMxWPG4jFj32DO4jFj8ZixeFrL2OObkR555BHU1ta6bLt06RIeeeQRj/rr7u5GSUkJCgsLkZKSAkmSnJbkt1gseOGFF7Bw4UJkZGQgKioKt9xyC1atWoVr16657Hf79u3Iz8+HXq9HTk4ONm7cCJPJ5LRda2srli5diuTkZERFRWHWrFk4duyYR8cQCPSh9meZ8YwZEREREZHWeFyY7dmzB21tbS7b2tvbsXfvXo/6MxgM2LVrF4xGIxYtWuRym/7+fpSWliIrKwsvvvgi/vCHP2DZsmXYtWsXvva1r6G/v1+1/ebNm7Fy5UosXrwYR48exWOPPYYtW7Zg+fLlqu2MRiPmz5+PY8eOYdu2bTh06BBGjx6NhQsX4sMPP/ToOPwtPPTzJfOJiIiIiEhbvLpc/tWrV6HXe7byRFZWFjo6OiBJEtrb2/Hqq686bRMZGYna2lokJSUpr82ZMweZmZl44IEH8N///d9YsmQJAFuh98wzz2DZsmXYsmWLsq3JZMK6devwk5/8BJMnTwYAvPbaaygrK8OJEycwa9YsAMDcuXNRUFCAkpISfPzxxyPKwdeMRqPykGkWZmIYjUblGmVPP+PkHmYsHjMWjxn7BnMWjxmLx4zF01rGbhVmH330ET744APlz6+++iqOHDmi2qa/vx+HDh1Sih53uXMznk6nUxVldl/96lcBAJcvX1ZeO3LkCAYGBlBcXKzatri4GGvXrsXBgweVMR44cAB5eXlKUQYAoaGhWLJkCdasWYPGxkakp6d7dDz+UFFRAdk8CICXMopSUVGhLLdaUFDg7+EEJWYsHjMWjxn7BnMWjxmLx4zF01rGbhVm//u//4uNGzcCsBVSrs5qAbazXzt27PDe6G7g+PHjAIApU6Yor5WVlQEApk2bpto2LS0NycnJSrt929mzZzv1O336dABAeXm5JgozAAj97KHSXPyDiIiIiEh73CrMSkpKsGLFCsiyjNTUVBw9ehS33Xabahu9Xo+YmBghg3SlsbERq1atwpe//GXcd999yusGgwF6vR7R0dFO+yQmJsJgMKi2TUxMdLmdvf1GysvLkZWVpVr1xWg0oqKiAgCQkJCAzMxM1T5VVVXo6+sDAKfqvb29HY2NjQCAzMxMJCQkKG0Wi0UpLGNjYzF+/Hjl74gKNwAw48LFGiQMNGPKlCkIDf387b127RouXboEABg7dixSUlJUf++ZM2cgyzIiIyMxadIkVdvly5dx9epVAEBeXh4iIiKUtp6eHlRXVwMAUlNTkZaWptr33Llzyk8qhp5NbW5uRmtrKwAgNzdX9fkZGBhAZWUlANv7MW7cONW+Fy5cQH9/PyRJUgppu7a2NjQ1NQGw/bBg1KhRSpvZbEZ5eTkA20o9OTk5qn1ramrQ3d0NAJg6dSp0Oh0AW8Z9fX3o6+vD6dOnkZ6ejuTkZNW+p0+fBgBERUVh4sSJqrb6+np0dHQAgLIojV1XV5eyoM7o0aOdHoBYXl4Os9kMvV6P/Px8VVtTU5Nyz+eECRNUn/u+vj5UVVUBAJKSkpCRkaHat7KyEgMDA9DpdJg6daqqrbW1Fc3NzQCA7OxsxMfHK22Dg4M4f/48ACA+Pt7pERnV1dXo6ekBYPsBSUjI57eyGgwGNDQ0AAAyMjJUZ8JHjRqF9vZ2WCwWVFdXIzc3V9VvXV0dOjs7AQC33HILwsPDlbbOzk7U1dUBsP0QJjU1VbVvWVkZLBYLIiIikJeXp2praGhQvusTJ05EVFSU0tbb24uLFy8CAFJSUjB27FjVvhUVFTAajQgNDVX9gAgAWlpacOXKFQC25Xr9OUfY6XQ6mM1mWCwWmM1mzhHw3hwBAB0dHbBYLJAkSZWBHecIm5HOEVarFWfPngUAhISEIDExUfUZ5hxhczNzRG1tLbq6ugDY3jur1apkzDnC5mbniPr6egBAeno6EhISVHMx5wgbb8wRMTExyM3NVWXsjznC/j11l1uFWWRkJCIjIwHYvrRpaWmqg/G1q1ev4t5774Usy3jrrbdUbxgw/OWRQ9s82dYVs9kMWZZVr8myrKwAaTabXe7jaoVIwPahsrdZrc6XJbrqNzMzE/ExTUBrP/qMJphMoU5jcuzXYnE+q2YymSDLMsLCwpzaLBaLsu9I+r3esTr2O/RYHTN01a89Q1fvkbv9evLeZGZmwmAwoLa2Flar1e33xlW/w31erpeh2Wx2+pwPPdaR9GsymVy2Ddevfd8b9evKcJ/vcePGoa2tTTXu641pqBsd6+DgIKxWq+p/kK76HWmGrjJyt19fzBF2er0eAwMDkGWZc4SX5wh7X/b+HP8xbMc5Qt2vK+5+vmNiYpyKCs4RNjczRzj2m56ervq+c45w7vdm35uhBTfnCHW/rrj7+bb/7phxdXW1X+YIT3i8+EdWVpanu3hVR0cHFixYgMbGRhw/ftxpYk5KSsLAwAD6+vpUFStgK+i+9KUvqbZ1dVbM/lMdV2fThgoNDXVZ7NknJsef5jnu42riAmw/BbS3ufoCXa/fuEjbn/uttv2HjsmxX1cfqrCwMMiy7HK8Op1O2Xck/Tr+fr1+XRXXw/Vrz9DVhOpuv756b4b2O9zn5XoZOm7jaLj3xp1+LRaLy7bh+rXvO1y/N5vhjY51qBsda3h4OCwWi5AMHX+iPJJ+A+VzyDnCud9AeW84Rzj3yzmCc8TQfjlHcI5w7DeQ5ghPSLIbpdy8efOwc+dO5OfnY968ecN3KEkjfg5Ye3s7UlJSsGHDBqdnmQG2ouzuu+9GbW0tjh07hltvvdVpmzfffBMPPfQQTp48iZkzZyqvt7S0IC0tDZs3b8aaNWsAAIWFhbh8+bJyOtVu69atWL16NRobG1WXJVitVuX0tF1sbKzLD4avlew/jbf/2oCnCidhxbyJN96BiIiIiIiE8bR2cKuicKzdrFarchmMq1+uTit6g70oq6mpwR//+EeXRRkALFy4EBEREdizZ4/q9T179kCSJNWz0oqKilBRUaFaFt9sNuONN97AzJkzna4VD2TxkbZKvbPf9SlaIiIiIiIKXG6vymjnuGy+txw+fBi9vb1KRXnu3Dns378fAHDvvfdCkiTcc889+PTTT/Hiiy/CbDbj5MmTyv4pKSnKQgGJiYlYt24d1q9fj8TERBQWFuLUqVMoLS3Fo48+qrpx9JFHHsGOHTvwwAMPYOvWrUhNTcXOnTtRWVmJ999/3+vHKUpVVRUGe64BYGEmSlVVlXLz6NAbcsk7mLF4zFg8ZuwbzFk8ZiweMxZPaxl7fI/ZRx99hNtuu83lCoy9vb3429/+hjvvvNOjPn/84x8rK/0AwDvvvIN33nkHAJRVZk6dOgUAWLlypdP+3//+91VnyNauXYvY2Fjs2LEDzz//PMaMGYNVq1Zh7dq1qv30ej2OHTuGkpISPP744+jr68OMGTNw+PBh3HXXXR4dgz/19fUhHLYbRVmYidHX16esCkViMGPxmLF4zNg3mLN4zFg8Ziye1jL2uDCbO3cu/u///k95uLOjiooKzJ071+VqJsOxL085HE9XNXniiSfwxBNP3HC70aNHY+/evR71HYiiw21XpbIwIyIiIiLSHo8Ls+EKJJPJFBALYXzRFBQU4FpkG/DxJ+jsd15ilW6eFp4Wr3XMWDxmLB4z9g3mLB4zFo8Zi6e1jN0qzLq6unDt2jXlzy0tLcoD8uz6+/uxd+9ep4fakW/YF//o4hkzIiIiIiLNcasw++Uvf4lNmzYBsC2HX1RU5HI7WZaVpejJt7gqIxERERGRdrlVmBUWFiImJgayLCsLZQx9Wrler8e0adM0tWhGMLEXZj1GM0wWK8J0vKSUiIiIiEgr3CrMZs2ahVmzZgGwrby4bNkyTT3jK9i1t7dj0Pz5gitd/SYkxej9OKLg097eDqvVipCQECQnJ/t7OEGJGYvHjMVjxr7BnMVjxuIxY/G0lrHHi39s2LBBxDjoJjQ2NsJkMiEyVEK/WUYnCzOvs2ccFhamiS+2FjFj8ZixeMzYN5izeMxYPGYsntYydqswe/311z3q9OGHHx7RYOjmxISHoN9s4X1mREREREQa41ZhtnTpUrc7lCSJhZmPZWZmwmq1IjGmB219vSzMBLBnzMdBiMOMxWPG4jFj32DO4jFj8ZixeFrL2K3CrLa2VvQ46CYkJCQAABJjIuiF5TsAACAASURBVIBWFmYi2DMmcZixeMxYPGbsG8xZPGYsHjMWT2sZu1WYZWVliR4HeQGfZUZEREREpE3aOK9HbuGzzIiIiIiItMnjVRkBoKqqCq+88grOnz+P/v5+VZskSTh27JhXBkfusVhsS+XHRugAsDATwZ4xAOh0Oj+OJHgxY/GYsXjM2DeYs3jMWDxmLJ7WMva4MCsrK8Ptt9+O9PR0XLx4EdOnT0d7ezsaGxsxbtw45ObmihgnDaOsrAwmkwkDXbYimYWZ99kzDgsLQ0FBgb+HE5SYsXjMWDxm7BvMWTxmLB4zFk9rGXt8KeOaNWtwzz33oLy8HLIs47XXXsPly5fx+9//HgMDA3jmmWdEjJPcEBNueztZmBERERERaYvHZ8z+/ve/Y+fOncqyk1arFQDwzW9+E0899RRWr16NDz/80LujpGHFxsbCbDYjOa4XwDVc62Nh5m32jENDR3T1L7mBGYvHjMVjxr7BnMVjxuIxY/G0lrHHo+zo6EBiYiJCQkIQFhaGjo4Ope3LX/4yNm3a5NUB0o2NHz8eANCMNgBNPGMmgD1jEocZi8eMxWPGvsGcxWPG4jFj8bSWsceXMqanp6O9vR0AMGHCBHz00UdK25kzZxATE+O90ZFHuFw+EREREZE2eXzG7Otf/zpOnDiBRYsW4aGHHsKGDRvQ3NyM8PBw7NmzB0uWLBExTnIDl8snIiIiItImjwuztWvXoqmpCQDws5/9DC0tLdi3bx8kScJ3vvMdPP/8814fJLln1GeFWe+gBSaLFWE6PqaOiIiIiEgLJFmWZX8PQiusViu6u7tVr8XGxioLofhLbW0tzGYzpBAd7t59HgDwt3V3IylG79dxBRN7xqGhocjJyfH3cIISMxaPGYvHjH2DOYvHjMVjxuL5O2NPawdtLFFCw+rq6lKe0ZAQFYaOPhPaeowszLzIMWMSgxmLx4zFY8a+wZzFY8biMWPxtJYxr3ULMmNHRQIAGjv6/TwSIiIiIiJyFy9l9ECgXspoNpshyzIkScJjb/4Dfzx3BRvvn4Lv35Ht13EFE8eMtfIsDK1hxuIxY/GYsW8wZ/GYsXjMWDx/Z8xLGb+AHD9o6QmfnTG7xjNm3sQJUzxmLB4zFo8Z+wZzFo8Zi8eMxdNaxryUMcik81JGIiIiIiLNYWEWZDI+O2PWwDNmRERERESaoa3ze+TStWvXYLVaERISgvRRUQB4xszbHDMeNWqUv4cTlJixeMxYPGbsG8xZPGYsHjMWT2sZszALApcuXVKWAh034RYAQHuPEQMmCyLCdH4eXXBwzFgLX2wtYsbiMWPxmLFvMGfxmLF4zFg8rWXMSxmDTEJUGCI/K8aaeDkjEREREZEm8IxZEBg7diwsFgt0Oh0kSUJ6QiQutvag8Vo/xqfE+Ht4QcExYxKDGYvHjMVjxr7BnMVjxuIxY/G0ljELsyCQkpKi+nP6qM8KM95n5jVDMybvY8biMWPxmLFvMGfxmLF4zFg8rWXMSxmDEJ9lRkRERESkLSzMghCfZUZEREREpC1+L8y6u7tRUlKCwsJCpKSkQJIklJaWOm335z//GY8++ii+9KUvQa/XQ5Ik1NXVXbff7du3Iz8/H3q9Hjk5Odi4cSNMJpPTdq2trVi6dCmSk5MRFRWFWbNm4dixY148Qt/js8yIiIiIiLTF7/eYGQwG7Nq1CwUFBVi0aBFeffVVl9sdO3YM77//Pm699VbExcXhgw8+uG6fmzdvxvr167Fq1SoUFhbi1KlTWLduHRobG7Fr1y5lO6PRiPnz5+PatWvYtm0bUlNTsWPHDixcuBDvv/8+7rrrLm8frhBnzpxRlgKdPn06z5gJMDRj8j5mLB4zFo8Z+wZzFo8Zi8eMxdNaxn4vzLKystDR0QFJktDe3n7dwmz9+vXYsGEDAOD555+/bmFmMBjwzDPPYNmyZdiyZQsAYM6cOTCZTFi3bh1+8pOfYPLkyQCA1157DWVlZThx4gRmzZoFAJg7dy4KCgpQUlKCjz/+2MtHK4Ysy8ovAMj9bCXGxmv96B4wITYizJ/DCwpDMybvY8biMWPxmLFvMGfxmLF4zFg8rWXs90sZJUmCJEk33C4kxL2hHjlyBAMDAyguLla9XlxcDFmWcfDgQeW1AwcOIC8vTynKACA0NBRLlizBJ598gsbGRjePwr8iIyMRFRWFyEjbmbKE6HCkxUcAACpauv05tKAxNGPyPmYsHjMWjxn7BnMWjxmLx4zF01rGfj9j5m1lZWUAgGnTpqleT0tLQ3JystJu33b27NlOfdhPdZaXlyM9PV3gaL1j0qRJTq9NTotDc+cAzjV14SvZiX4YVXBxlTF5FzMWjxmLx4x9gzmLx4zFY8biaS3joCvMDAYD9Ho9oqOjndoSExNhMBhU2yYmOhct9tcct72e8vJyZGVlIS4uTnnNaDSioqICAJCQkIDMzEzVPlVVVejr6wMAFBQUqNra29uVM3WZmZlISEhQ2iwWi1JYxsbGYvz48ap9a2tr0dXVBQDIGx2DYxWtON9s+/O1a9dw6dIlALaH7Q19rsOZM2cgyzIiIyOdPsSXL1/G1atXbf3m5SEiIkJp6+npQXV1NQAgNTUVaWlpqn3PnTunXNtrv4TUrrm5Ga2trQCA3NxcxMR8/jDsgYEBVFZWArC9H+PGjVPte+HCBfT390OSJKdrhtva2tDU1ATAdqnsqFGjlDaz2Yzy8nIAQFxcHHJyclT71tTUoLvbdpZx6tSpqgcSdnR0oL6+HgCQnp6O5ORk1b6nT58GAERFRWHixImqtvr6enR0dACAsiiNXVdXF2prawEAo0ePxpgxY1T7/j975x0mR3Hm/8/ksDnMJu1KWsVVDgQRJECIIIJJBnwYjAHrZ2OO092RTJKFAZ11RgYjThzYRBswNjKcZbCwAZNBoLhW1kra1Wpz3tnJ0931+2M0zfTOKiHN7krU53n2AU11vVP17Z63++2qemvz5s0oioLD4aCiosJQ1tDQQGtrKwCjRo0yXPeBQICqqioA8vLyKC0tNdTdvn07oVAIi8XCxIkTDWUtLS00NjYCMHz4cLKysvSySCTC1q1bAcjKymL48OGGurt27cLn8wGxFySJo93t7e3U1dUBUFpaSl5enl6maRobN24EID09nZEjRxrs1tTU0N3dDcC4ceOw2+16WXd3t54MqLi4mIKCAkPdTZs2oaoqTqeTsWPHGsrq6ur03/ro0aNxu916md/vZ+fOnUBsL5SSkhJD3W3bthEOh7FarUyYMMFQ1tTURHNzMwDl5eWDzkdMmDABq/WrW4D0ETGkj/gK6SNiSB8RQ/qIGNJHfIX0ETEO5CPiv9ND5bgLzIADTo3sXXY4x/aFoihJ81aFEHoGSEVR+qzTV4ZIiF1U8TJN05LKD9VuRVEsuNyyLzBLtKuqap92hRDYbMnr0VRV1ev27uuh2N1fXxPt9u5rooZ92Y33ta9zdKh2B+rcHOh62Z+GiqL0OZ33QOfmUOxGo9E+yw5kN173YHb74lA17Kt+Ypt6c7C+RiIRNE0z3CD7svt1NexLo0O1O1iuQ+kjku0OlnMjfUSyXekjpI/obVf6COkjEu0OJh9xOBx3gVleXh6hUIhAIGCIWAE6Ojo44YQTDMf2NSoWf6vT12hab6xWa5/BXtwxJb5tSqzTl+OC2Fq6eFlfP6BDtTu+KPbmbVtTD4qqGez2dVHZbDaEEH3atVgset3efT0Uu4n/3Z/d3n1N1LAvu/G+9uVQD9XuQJ2bA10v+9Mw8ZhEDnRuDsWuqqp9lh3IbrzugeweqYYH62tvDtZXu92Oqqop0VDTtMP+3QzG61D6iGS7g+XcSB+RbFf6COkjetuVPkL6iES7g8lHHA4mMYjSlLS1teHxeFi4cGGfe5nFWbJkCXfeeSfV1dVJw5+vvPIK1157LatWrWLGjBn6501NTRQXF7No0SLuvfdeAM477zz27t2rD6fGWbx4Mffccw/19fWGaQmapunD03EyMjIOOTFJqti7d6/+w4gP1WuaYNIDf8MfUXnnP89gdGHGgLbxWKcvjSVHF6lx6pEapx6pcf8gdU49UuPUIzVOPQOt8eHGDgOelfFoM3fuXJxOJy+88ILh8xdeeAGTycRll12mf3b55Zezbds2Q1p8RVF46aWXmDFjRtJc8cFKR0cHbW1t+kgfgNlsoqI4NmoWn84o+fr0pbHk6CI1Tj1S49QjNe4fpM6pR2qceqTGqedY03hQTGVcuXIlfr9fjyi3bNnC8uXLAbjwwgtxu920trby4YcfAugL+1auXInH48Hj8eibQefm5nL//fezYMECcnNz9Q2mH3jgAebNm2dYOHrTTTexbNkyrrrqKhYvXkxBQQFPPvkk27dv59133+1PCVLC+OJM1u7pZEujl0unDv7skhKJRCKRSCQSyTeVQTGVcfjw4Xqmn97Epyt+8MEHzJ49u89jzjzzzKQNp5cuXcqyZcuoqamhqKiIG2+8kfvuuy9pbmhzczN33XUXb775JoFAgKlTp/LQQw9xzjnnJH3PYJ3KGAqFEEJgMpkMmY5e/bKWu1/fyMnlufzxR6cewILkYOxPY8nRQ2qceqTGqUdq3D9InVOP1Dj1SI1Tz0BrfLixw6AIzI4VBmtgtj9q2wOc8cj72Cwm1v/0PNIdg2KAVCKRSCQSiUQiOe75xq8xk3zF0Dw3Q3PdRFXBF7sPviebRCKRSCQSiUQiGRhkYHacM2t0bPPCj3a0DnBLJBKJRCKRSCQSyf6Qc9uOA3w+H5oW26sscdd7gFmjPbz8RS0fV7UNUOuODw6kseToIDVOPVLj1CM17h+kzqlHapx6pMap51jTWAZmxwG7du0iGo1is9mYMmWKoezUkXlYzCZ2t/nZ2xGgLNe9HyuSA3EgjSVHB6lx6pEapx6pcf8gdU49UuPUIzVOPceaxnIq43FOlsvG1LJsAD6U0xklEolEIpFIJJJBiRwxOw4oKCjQdzXviznjCli7p5MVGxq47pRh/dy644ODaSw5cqTGqUdqnHqkxv2D1Dn1SI1Tj9Q49RxrGst0+YfBsZYuP05jd5DTFv8DIeCjO2czNE9OZ5RIJBKJRCKRSFKJTJcvSaI4y8XpI2PZGV9fXzfArZFIJBKJRCKRSCS9kYHZN4RvnzAEgNfX1SMHSSUSiUQikUgkksGFDMy+IZw/oYg0u4XajgCf7JSp8yUSiUQikUgkksGETP5xHLBlyxY9Fej48eP7PMZtt3LViWW88FkNS9+rYuaofEwmUz+39NjlUDSWHBlS49QjNU49UuP+QeqceqTGqUdqnHqONY3liNlxQDQa1f8OxM1njsRuMbO6ppPPd7X3U+uODw5VY8nXR2qceqTGqUdq3D9InVOP1Dj1SI1Tz7GmsQzMjgNsNpv+dyCKspxcc3IZAL96t0quNTsMDlVjyddHapx6pMapR2rcP0idU4/UOPVIjVPPsaaxTJd/GByr6fITaeoOccYj7xNRNJ68djoXTioe6CZJJBKJRCKRSCTHHTJdvuSAFGU5ufmMEQA8+Jct+MPKALdIIpFIJBKJRCKRyMDsG8gts0dRluuiyRvisXd2DHRzJBKJRCKRSCSSbzwyMPsG4rRZePCSiQA880k1729rGeAWSSQSiUQikUgk32zkGrPDYLCuMWtsbERVVSwWC8XFh75mbMH/beJ3q/aQ5bLx5r/NpCzXncJWHtt8XY0lh47UOPVIjVOP1Lh/kDqnHqlx6pEap56B1vhwYwe5j9lxQEtLi75Hw+FcdPdfPI5/1ndTubeL65/7kld/eAqFmc4UtvTY5etqLDl0pMapR2qceqTG/YPUOfVIjVPP0dbYF1Zo6wkjgOF57gHZr3Zni4+Pq1oZludmpCcdm8VMfroDu7XvQEQIQUN3iO1NXva0BzhhWA6TS7PZ2dLDjmYfJw7PoSDj6z+bHmvXsQzMvsE4rBb+99rpXPXU51S3+bnmN6t49f+dQoEMziQSiUQikUi+FmFFpbUnjKZBlttGa0+YmjY/nYEIIUUjw2FFE4L127y0+qN0hQWZlWuwWkx4gwoRVcOT7sCT4aAw00lJtpPSHDeTS7OwWZIDHCEET/xjJ0vfq0LRYhPhhmS7OHVkHiXZLjKdVmwWM+OKM5k2NJtAWKW+K0hDVxBPhoPJpVmHHMQJIWj3R7CaTWS77fSEotzz+ka6g1FsFjPvb2+h91y8HLeN/3fGCLoCUd7b2ozdaiHNbqEnpNDQFaSnVyK6ccWZbG30Gv49sSSTaUNzOGVELjaLGUUTDMt1YzYb2x1VNd7Z0syzn1Tzq+9MPaQ+DSbkVMbDYLBOZfT5fGiahtlsJj09/bDr7+0I8C+/XkV9V5BRBen8/v+dgifDkYKWHrscqcaSgyM1Tj1S49QjNe4fpM6p53jXWAjBrlY/PaEoDqsFu9VMusNKYaZjv0FKhz/CrlYfHf4IUVUjzW6lJ6xQ3xlkW5OXHc0+mr0hOvyRlLTZk+HgoknFhKJfBVbpDitZbjsf7WgFIM1uQdEEYUXr04bZBFqvJ/+pZdmMLczAG4oypSybyaVZrK7uJBBRuGBSMVNKs/BHVJ74RxW/+3wPgYiKyQT/MWcM62o7+XDfd8eZUZ5Lhz/C3s4Aiir0YHF/WM0mRnrSKch08OnONjQBJhOMyE9jV6t/v/Xy0uycXJ7L0Dw3douZZm+I97a20L5P/x/MLOc/zxo6oNfx4cYOMjA7DAZrYHY0qG0P8J1ff05jd4jRBem8eNPJlGS7BrpZEolEIpFIUoCiakRUDZfNMiBT3voTIQRtvggRVaPZG2LV7nZWbGhgW1NP0rGZTisjPOlku210BqLUtPmxmE1YzCZae8KH/J12ixmzGUJRDbfdQnl+GvnpDpw2M759I0RFmS6Ks5x6MKhqgkyXFavZTGtPmJaeMC3eEPVdQXY099AZiO73+0wmePDSiXzvlGGEoiqfVLWxtdFLkzeEP6zgC6us3dOh28hLs1OU5aSqxUdkP0FcHJfNgkAQivZ9nMtm4SdzxxJWNE4flc/EIVl6maJqvLG+nle+rCUvzc4V00tJc1gJhBUynDY8GQ7K89P0qY67Wn18tqudU0fkMaognRZviPV7u9hc382q3R2s39uJxWxCCPYbfOan2/nuyUO5/rTh5KcP7ECDDMxSyPEcmAHUtPn5l1+voskbwpPh4JnrT2RKWfZAN0sikUgkgwhNE9R1BhEIzCYTJlPsIdRhtZDhtBqmFjV2BwlFtQFb7xJnU303rT1hThieQ6bTNmDt+LqEoiob67vxhRSy3TbGl2TisFoACEQU1td28WV1BwK4YGIRFUUZmEwmmr0hPtjeQiCioqiCiKqxpdHLpzvb6Nr3gO6yWRiS42J8cSZjizLIcdup3NvFe9taUDSNLJeN8cWZTCrNojDDSX6Gg7w0O4WZTvLS7ElTyQ6X2vYA6/d2MmdcIemOr7/CRtUEPaEo2W473YEoL35eQzCqMizXzWtr61i7pzOpjt1qpiDDQVjRCEdV/BEV9SCjO6U5LjwZDmxmM4GogttupTjLyZjCDCqKMhiS46Iww0m224bJZCIUVXFYzUd8/cen6H2xu528dAcl2S5Kspy0+sJU7u3mjDH5nDW24IA2NE3Q0B0kL82Byx67ftp8YV5fV0c4quGwmfloRxs7mns4YVgONouZv21u0gOgobluFlw8njPHeHh9XR0L/rwJRRM8fd0JnDeh6Ij6d6gIITCZTEQUjfW1nWxq8FK3b2Qux21j2rAcZo3Kx9rHlM+BQAZmKeR4D8wA6joDzHtxDduaerBbzNx9QQU3nj78uH+bJpFIJN8UGrqCrK7p0NeB9OXeTSYTQgg0IegORGnsDqFqgqiq8fctzTR2h/q0bbOYKMhwkuaw4AspNOw7Li/NzknDczm5PPY3rjgTyxE+0AP4wwrN3hBpDmufyat8YYVH3t7Gi5/vAcBiNnHmGA/zZpZz6sg8w70tnoRgS4OX8vw0RhUMjul7O1t6+P5zq6nvCuqf2SwmSrJduO1Wqpp7kqaKlea4GF2Qzqc724moBx4NORLsFjNFWU5GeNK46/wKxpdkArGA/N0tzRRmOpkxIo//W19PZV0XPzxjBBVFsWP2dgS4/bVKvqzuAKAs18WSK6cwY0TeYbVB1QR/WlfH//xjJ7UdASaUZNLsDdPmM45umUxgM5tJd1o5YVgOZ4zxcMnkErLcXwXqYUWlqtlHXWcQbyhKmt3KCE8a5n0BVrkn7ZgM7I+EQEShrSdCRFUZlpdmWONW0+bHH1GYUJJ1AAvfbGRglkIGa2AWCoX0NwhO55En7ugJRbn9j5X8fUszAGdXFPDIlZPJG+Dh4IHkaGssSUZqnHqkxqlnIDRu9obY3NBNbXsATcQe2q0WM5nO2MiK1WxiR3Msw9naPR38Y1tL0hqTw8VuMWO3mlE1gSoEiqr1aTM+Baz3VKlMp5V5s0bwLyeV8fnuduo6Y0FHRVEGs0Z78IUVPtnZxooNDXT4w8wa7aE4y0lDd4hwVKXDF2L1ni5q2gO6zall2ZTluukORukORGjzRQzBTGmOS/8egAklmdx0ejlnjvWwsa6bRX/dys4Wn14+wpPG+ROKuGhSsWFqViL+sMJbGxvp8Ee4ZErJfpcA/HlDPf+3vp42X4SheW6uPKGUVm+YL6o7qO3wowm4fNoQhua6+WhHK5sbvOxp9+PJdFLT5qc7GCXHbWNIjovGrpC+hiZOcZaTGeW5BCIqH2xvNQRjU0qzKM2NrcGxmk0UZ7s4c4yHkZ40rBYzbT1hqtv9bK7vpqY9QKc/QlGWk3PH5pGfbqfNH2Frc5DtTV7a/RFae8K0+SK0+8OGJA/pDiv/cc5oPq5q46Oq1qQEEBBbSzRv1ggunFTEra+sp7YjgNkEWS6bPsVuaK6bM8bkc8ZoD7NGe/SRnb4IRBT+7ZX1vNfHfqwjPWmcOCyXna0+ThyWww9mlg+65GbSJ6eegdZYBmYpZLAGZpWVlXoq0ClTphwVm0IIfrdqDw+/tZWIolGQ4eCO88ZyydQSnLb9O8njlVRoLDEiNU49x5LG8Qf5/aVYPhg9oSi1HQFavGHcdgvFWS6cdjM2sxmrxYTNYsZsMrGxvptPd7bRHYwSiKi0eEMI4NzxhZxdUUBBxv4TAfRFf2msaoJmb4jffLyb336+56DTr3ozpTSLTJdNf3gWfFU/8anAYjaRZrdSku3CZjWhqIITh+Uwu6Ig6V4QUTRafWGavSFCERWL2cSEIVnYLCY21nXzZU0HX1Z3sKamU19j0xcOq3m/a0f6Is1uIRBV+wwEIPag/9BlEzlzjIfdrT5e+KyG19bUEYyqScdazSZGeNKobvMTVb8yeM3JQ1lw8Ths+4KbnrDC0x/u4sXP9uh9sZhNnF1RwPkTipg7sUiflvfB9hZueH71IfenL6aWZfPcDSeRm2ZHCLEv8UOI7mCUiqIMSnNc+nXqCyus29PJtiYv04fmcOLw3K/1nQe7liNKbL1WQ1eQR9/ZwRf7Rr7inDAsh70dAVp6wpTluhiel8bHVW2GY4bmunl53gyy3TYWvbWVP62rM+iel2bn5jNHUp6fRkTVYokuXDYyXTY21Xfz9Ee72FTvxWE1c9u5Y7h4Sgkf72jFbDZx2dQhX9t/9BfHkk8+VhlojWVglkK+SYFZnK2NXv7t9+v1t4j56XauO2UY350x9Ij2lTjWGOgf9jcBqXHq+Toaq5qgMxDBG4xiMpmwmEyYzbFF1z0hBafNTI7bTrbbpq952R9CCFp6wrFpQsEowahK5d4uNtZ3k+O2U5rjIt1hZWerj79vbkbRNEZ6YtPJQlGViqJMZozI5aJJxXgyHDR7w2xp7Kaq2Yfd+lWgtWFvF7tafft9UD8cnDYzU8uyOXd8EblpNqKqQFEFTpuZMYUZjCnMMDz8Ha3rWNUEH+5o4U9r6+kKRshx2/GFFT0hQLsvbBihGluYQXl+GjarGUXViKqCVl+YrY1ehBCM9KQzujCDsYXpnD+hiNGFGUciyxGhaoK3Njay+K9baegOMaYwnall2Sia4JOqNlr2JVgYVZDOBROLKM1x8cH2VgIRlZJsF+kOC53tbYzINjO5KI2ZJ0+jpSeWjc0fVsh228l22chJs1Gen05umj2pDV2BCC9/UcufN9Szo9mH1WziBzPL+dezR5HptNETivL+9lbe3tTIyk1NScFq4ijgsDw3hZlOfUoexKblPX3diWS6rFz6P5/S7o9w6dQSLppUzMdVbby9uYmSLCdnjPEwpjCDlp4wv/+yFn9Y4YzRHk4cnkN5fhrN3jBRVeP8CUUHHDlKBYdzLYeiKve9sYm1ezq4eHIJV55QyvD8NFRNsLcjQGmOC4vZxN+3NPPcJ9V8Ud1BUaaT124+lbJct27HF1b4fFc7H1e18t7WFsOI5/7Icdt45vsnccKwnCPuc39zqBqrqkp7ezvh8KEnH5HE6Onp0UfMMjJS4/ccDgd5eXlYLMm/URmYpZDBGpjt3btX39W8rKzsqNsPRlR+t6qGFz6t0dcLAIwuiN3gbzh94LPepJpUayyRGh8toqqGEMaRJkXV8IdVvO1Nh6Sxomps2NvFK1/U8ubGxoNm7IqT6bQyviST3DQ7jd0hbBYzRZmxjGMAKzc1GaaSfV3MJsh22w+akjqeoMAfUWjqDhHZp03vNs8a46Esx43TZqYgw0lXMMKblY1sa/IedMpfbpqda04u47KpQxhVkE5dXd0BNRZCUNXiY3erH00IvT1luS7K89N4d2szKzc2sWp3O97Q/keV4jqMK87k7gsqmDXa0+cxyr4pbYNlIXwiUVWjOxg13D9UTbCr1UdRlvOAa3mOpr/oCkQwmUxkufr+vs92tnHHa5WG+x/EpsrdNbeCc8cVYjab2Nbk5a8bm1i+Zi8N3SGsZpO+9mtccSZv3HLaMTXjJJU+0nJArQAAIABJREFUuak7hNthOeA5jqoar6+r49XVe9EEOCxmvKFobKpqMEphppO5E4u4dsZQSnPc+7UzmDkUjYPBIK2treTn5+NyueSa/8MkEonogZndnvyS5kgRQhAMBmlra8Pj8eByGaczy8AshQzWwKy/iKoab29q4rlPq1lf26V/7rCamT22gNkVHiYNyWZUQfqgnz4gkRyLBCMqnYEIgYgSC7RCUXa1+Khu89Pmi7Cnw8/2plgigMIMJ5mu2FSqmvYAEUWjOMvJSE86NktsncnEkix9I1RFE3iDUXa1+tjc4CUQMU7zytg3LUsVsT1pHFYzGQ4rIUWjKxA55DVLFrOJokwnOWk27BYzIz3pnDAsB19YobE7RCCikO6wctHkEvLT7VQ1+7CYTVjNJjbUdfHulmbW7fM/FrOJkZ40xhRmIIBwVGNccQZTSrOZUpbd536M8QQWUVVDUQUZTut+g5aIolHbEeCD7S18srMNVRP6VLbuYJStjV5D8JTttumZ7yqKMphRnssNp5fzzuYmlv5jJ4qqYTab9Gx4ByPHbeOK6aVMKMmkwx8h3WGlINNBQYaTggwHeemOo5JAQ3JwFFWj3R/BYTUTimr4IwrD89L61L8rEGH+qxv0faUmDcli6TXTKM9P6+9mS44D6uvrKSgowGb7ZiUdOdaIRqO0tLQwZMgQw+cyMEsh3/TALJEOf4SPq1p57tMaKvd2GcpslthGgRVFGYwuzGBqWTYnDMs5pt4USo4vYtnlOOSH2LCisqG2i/wMB0OyYwkDekJRMl02hmS7Dvta9ocVdrX6CO9bk1Hd6iesaJhMsex33mCUNXs66PRHKct14clwkum0MrYogyHZLl5fV88n+9ZB9ReZTivnjCvke6cOY9KQrAOOuGiaoCekUN8VZFNDLKV3UZYTRRM0d4do9obwRxROH5XPnIrCI56StbcjQFcgyujC9AH1K4qq8e7WFl75spYvdrcf8rooh9VMRXEmdotJz364vakHb0ihNMfFt6eXMruigIklmYNypEtycLR9I3/56Q5y+phKKZEcKnv37pWzSI4R+jpXMjBLITIwS0YIwcb6bt7b2sLnu9rZ2uSlp4/pN3aLmSy3jUxnbBH5uOJMvj29lLFFA7fOQTI4UDVBKKoSiqoEoyphRSPHbSfHHUtMoGgCm8WEL6xQ1eKjqTtEhz+ComqEFI2GriD1nUHqu4KomiDbbcNsMiGIJQWIqoJNDd10B6Pkuu247Bas+9aI2Cxmslw2rBYTjV0hLGYT5flprNnTud9pcml2C3MnFjN3YhHTh2azpyPAP/d28c/6bpq9ITQNHDYz6Q4rGU4rPSGF97a29Jlo4Otgs5hIc1hJs1tJc1gYmhtL612Y6aA4y8mEkiycNgv1XUECYQVFEwzPSyMnzcamei+N3UGiqsbuNj9bG3tIs1sozHRit5px2SyM8KRRUZTJ6IL0I96f6JtEKBpLs+12WDABmxq8vLxqD19Ud+CyWbjnwgpOG5lPKKoyujA9aT2epsXWhHnSHVJ3iUSiIwOzYwcZmPUzMjA7OPFsUVsbe6hq6WF7Uw+rdrfT7O17werYwgymD8smzW5F0QT56bE1IUVZTgoznXjSHWS5bPJBpZ8IRVV6Qgo9oei+/yoomkaG04rFbCaqarT1hGnsDtHYHaQrEMVmNeOwxlJn28xmzPtGgSKqRk2bn9aeMKqITZNr6Qkb1isJwX732LFZTHp2rsS1Gv1FbpqdQEQhFNVw2y3kuO10B6MHzCZ3IPLT7aQ7rOSm2RnhSSfdYdVH8uxWM1PKsinJcrK3M0C7L0JXIEplXRe7W/2cOdbD1SeWMcKTRobDKtcYHENsqu8mL91OcVbfadQlEonkQMjA7NhBBmb9zGANzHbs2IGiKFitVsaMGTOgbemLeLAW21smSl1nkPe2NfPu1pZDSvFsNZvIT3eQn2GnKNPFCcNymFCSidUSyxBnMcemA9ksseNy3HYiqkZ43+iLzWImw2nFbbd87QfawaCxti87XqsvTFtPhFZfCF9IwWw2Ydaz5Zkwm2JT9tx2K1N7rbMJRVUauoK0+SKYTVDfFeS9rS1sbfRS1xk8aqM6Xxe7JXYe/ZG+g7XCTAdlOW5y0+yxQNBipjjLyZAcF0OyXdgtZrqCUTQhMGHCH1bQhGBCSRaFmQ7afBFCioqmxdZJRVWNrkCUiKJRku0ipKjsbPZRnp/GWWM9+jTDbLdNn3K2dk8nKyob+GhHKzXtAfLT7UwuzWZyaRbD8tyYTSbCioYvpOAPK6hCcNbYAqaUZg14QDUYruPjHalx/yB1Tj1S49RzKBrLwOzI6M99zI5GYGZNWesk/UYwGNTTrQ5GTCYTpTluShMy2V59UhntvjCrazrZWN+FqsUyjLX2hGnyhmjqDtHqC9MViKJoIvaZN8Smei/vbm3+Wu2wmE369LJsty2WgGDf1LbcNDtFmU6sFjOaECBi+/poIjaqU7u3Vc+cNKrHTZrdgtthjf1335Sy+H+jimBdbSfVbbF1RBFFI6KqqBqYTLFMcVkuG2FFIxhRCURULGZw2a10ByL7+hqOrc3pCRGKqtgtZvwR9bD3KgLIT3eQ5rDQE1IOmsUuTsY+nTKcNizm2DRCVRNYLSZy0+yUZLkoznKSk2ZHUQVhJRYEq5owrOcqy3VTkuXUtS/IdOKyW4i/DzKZTLhsFpw2M9u3bEJVFGw2G2PHT9QX2tvMZgJRBbfNSpb7yK7xQ9lcdPbYAsO/E9eHmEwmThyeq+8L5AsrpB1BwN/fDHZfcTwgNe4fpM6pR2qcer7JGh/qffP999/nrLPO+trfo2maHpgdjFAohMvl4vbbb2fJkiVf+zuPhAEPzHp6enjooYfYsGED69evp62tjYULF/LAAw8kHbtu3TruuusuVq1ahdVq5eyzz2bJkiWMGDEi6dgnnniCZcuWUV1dTUlJCTfccAP33ntv0sXf0tLCXXfdxZtvvkkgEGDKlCk8/PDDzJkzJ1VdPuqYTCb971giL93B3ImxjTj3R0TRaPeHae0J0+YLU90WYNXudmrbA2hCoAqBpsUCgYii0eYL61PeTKbYIvuoKlC12F88zW5dZ5BN9d6v1/A1XQc/5igTin41gpSbZsezbwQxw2FDIFA1YnpoAk3E/tp6Iuxo6aHNF6bN95Utt91CQYZj3xosK2eO9XDKiDzKclzkpTtId1gHJNObxWxG23cdO20WhmR/NfUri8F504pvIHuscKz6imMJqXH/IHVOPVLj1PNN1vjzzz83/Puhhx7i/fff5x//+Ifh8/Hjx/dnswacAX+qaG9v59e//jVTpkzhsssu45lnnunzuG3btnHWWWcxdepU/vjHPxIKhfjpT3/KrFmz2LBhAx7PV3u4LFq0iAULFnD33Xdz3nnnsXr1au6//37q6+v59a9/rR8XDoeZM2cOXV1dPP744xQUFLBs2TLmzp3Lu+++y5lnnpny/h8NJk+ePNBNSBl2q5niLJdhfcYPZpbv93hNEwT2jTDZEjKeBRPWTnlDCp3+2MhUdzBKMKLS5gvT7A2jakJfI2Ui7jRjo3kmTAgEwahGIKzgj6h62vJgJPbvOMPz3IwvycRls2LftwbLYjahaoJ2f4TuYBSXzYzbbsVpi40g+SMqWS4rhRlOCrOc+/Z/cuK2WwgrGukOK3npdmyHkaWtOxClritAMKKS5rBSkuUi0zU41ygdz9fxYEFqnHqkxv2D1Dn1fNM1PtRRliPhcDROnGmS+JmiKAghMJvNWK3Gx/pQKKSPGKWlGbdrCIfDhEKxvflcLpdhj6/E6XdWqzWprt/vR1Fi6617T8uLRCIEg7H9Kp1OJw6HcduS7u5uACZOnEh6err+ucfjwWw2M27cOADS09MNGzZHo1ECgQAQ29DZbDZjsVj0Y7xeL5qmYTabyczM1Ou53cfYHndigNE0TWiaJoQQorW1VQBi4cKFScddddVVIj8/X3R3d+uf1dTUCJvNJu666y79s7a2NuF0OsUPf/hDQ/1FixYJk8kkNm/erH+2bNkyAYjPPvtM/ywajYrx48eLk08+OakNqqqKrq4uw5+qql+775LjC1XVhD8cFd3ByEA3RSLpFxRFEcFgUPh8PhGNRpPKGhoaRF1dnWhtbU2qW1NTIzZu3CgqKyuFoiiGsubmZvHxxx+LDz74QNTX1xvKVFUVK1asEG+88Yb44IMPkux++OGH4rnnnhPPPPOM8Hq9hrLdu3eLRx99VCxZskSsWrUqqe6tt94qrrnmGnHLLbcklb344ovi6quvFldeeaWoqqoylO3YsUNcdNFF4sILLxT/+7//m1R33rx54rzzzhOXX355Utlrr70mLrroInHZZZcltamzs1P86Ec/Ev/6r/8qnn322T7b9PDDD4uf//znSfei1atXi4ULF4qf/vSnYu3atYayaDQqFi1aJP7rv/5LvPzyy0l233zzTfGrX/1KPP7446Knp8dQtnPnTrF06VKxdOlSsWbNmqS6Tz75pHj88cfFSy+91Kfdn/3sZ2LhwoWiqakpye78+fPFrbfeKt54442kuosWLRI//OEP+zw3zzzzjDjnnHPEGWecITZs2GAo27Ztmxg+fLgYMmSIuPXWW5Pq/uAHPxAzZswQp59+elLZa6+9Js444wxx5plnivfee89Q5vV6xbnnnivOO+88cf/99yfVfeCBB8S3vvUtcckllyRdh++99564+OKLxfnnny9WrFhhKFMURVxyySXiwgsvFLfddluS3XvuuUdMnjxZjB8/XuzatctQ9vHHH4tJkyaJcePGiSeeeCKp7sknnyxGjhwpZs+enVT2yCOPiEmTJonJkyeL9evXG8qqq6vFOeecIy644AKxbNmypLrXXXedOP3008V5552XVPbUU0+JMWPGiIqKiiQNm5ubxbRp08S0adMMz3FxbrrpJjF58mQxefJkEQ6HDWXLly8XEydOFBMnThR/+tOfDGWhUEiMGzdOjBs3Tlx//fVJdufPny/GjBkjxowZIxobGw1lb7zxhvB4PMLpdIqlS5cm1fV4PMLtdosTTzwxqWzRokVi6tSpYvr06WLbtm2GsjVr1ojRo0eLUaNGicWLFyfVnTlzphg2bFifz57vv/++WLNmjVi9erXhGVgIIQKBgFi9erVYvXq1qK6uTqq7efNmsXr16j5/q01NTXrdtrY2Q1k0GtXLduzYkVR3x44denlv39/e3q6X9f6dCyH0ssTncSGE+P73vy/cbrdeHggE9LKVK1cKQCxatEh85zvfEQUFBcJkMonq6mrR0NAgfvSjH4ny8nLhdDpFbm6umDNnjuHZPlGvBQsWiDFjxgi73S7y8vLE2WefLb788kshhBDBYFAA4vbbb9frqKoqbrvtNmGz2cSLL76YZDOR2trapM8ON3YY8BGzQ3kboSgKb775Jtdff70hCh42bBizZ8/mjTfe4L//+78BePvttwmFQtx4440GGzfeeCP33Xcf//d//6cPi77xxhuMHTuWU089VT/OarVy3XXXce+991JfX5+0UdxgxOv16m8Keu86HolEqKmpQQhBRkYGJSUlhro7d+4kFAphMpkYP3684XwoiqK/BRFCGN5cKIrCtm3bUBSF9PR0Ro0aZbC7atUqGhsbURSFyy67zDCFdOvWrbz99ttEo1Fmz57NSSedZKi7bNkyotEohYWFXHPNNYayFStWsGHDBlRVZf78+eTl5ellu3bt4vnnnwfgrLPO4pxzzjHU/cUvfoHP5yM7O5vbbrvNUPb3v/+dzz77DIhdK8OGDdPLGhoaePLJJ1FVlRkzZnDZZZcZ6j7wwAPU1dXhcrl44oknDGUvvvgiTz/9NKqq8sgjj3DGGWfoZW1tbcydOxeTycTs2bP5xS9+Yah72223sX79ekwmE2+99ZbhvL777rs89thjmM1mbrnlFi644AK9TNM0rrnmGkwmExUVFUnTgp9++mm+/PJLzGYzP//5z8nPz9fLvvjiC5YuXYrFYuGKK65I6uv8+fNRVZWioiIWLFhgKHvzzTf54osvALj55psNv529e/fqo9WnnnoqF154oaHu0qVL6ejowO12c9dddxnKPv30Uz7++GPMZjNXXnmlYepye3s7TzzxBKqqMmXKFK688kpD3UceeYSamhogNr058a3eZ599xvLlyzGZTFxzzTWceOKJepnP5+Puu+8mEokwfvx4/uM//sNg98EHH9T7+vLLL5Odna2XffjhhyxevBhFUfjxj3/MFVdcYag7c+ZMotEoY8aM4Xe/+52hbNGiRfzlL38B4JVXXjH0de3atdx8880AfP/73+fWW2811J07dy7Nzc0UFhby9ttvG8oef/xxnn32WQCeffZZw29u69atXHTRRUSjUa699loWL15sqDtjxgw2bNiA0+nU33TGeeyxx7jzzjsBWL58Od/+9rf1stbWVt3fXHbZZbzxxhuGuvPmzePdd98FYlPaE9+crly5khtuuAGAJ598kh//+Md6mRCCSy65BIDTTjuNTz/91GD3qaee4ve//z0As2fPJiPjqy05tm3bpv/2H3zwQWbMmGGo+/LLL9PZ2cnIkSPpzbp16/jjH/8IoPc5Tnd3N2+99RYA5eXJI/off/wx27dvJysrK6lsx44det3e9y2v18vTTz8NwFVXXcVNN91kKH/22Wf56KOPALjjjjsM1/fatWv52c9+BsTuldOnT9fLotEo9913HxDT6Lvf/a7B7nPPPcfrr78OwJVXXmk4Nxs3bmT+/PkALF68mBNOOMFQ984778Tv9zNx4kSuvfZaQ9mKFSt0P3DFFVdQWFiolzU0NLB06VIg9pa9t+959tln2b17N8XFxSxbtsxQtmvXLv1aam9vN5Rpmqb7AJ/PR282bNjA2rVrDfe3OHV1dbq+LS0thrJIJMI777wDkDRKAbF7YPx3GB9ZSOzrm2++CcDFF19sKDObzaxYsQKAjo6OJLt79+7ln//8JwCqakzW5Pf72bhxIxD7/fWmurqa1tZWNC05uVJDQ4NeNz4qEaezs1PXt6/re+3atWzdutXwW4vT3t7Ojh07gGT9w+Ew69evB0h6hoDYeY33VfTKU9fZ2cmmTZv0/09ECMHWrVsBKCgwrhmO9zXept7nBr7SrnfCBohpEwgE9BGhRGpra9mwYQOAPhIVJxgMUlVVZbCfSF1dHXv27OnTbrxPfbF06VIeffRRAH71q18xfPhwvay6upqzzz4bIQRnnXUWf/jDHwx1r7/+er29W7ZsMZS9+OKL3HvvvQAsWLCA0aNH62U9PT3MmjULIQTTpk3Tr+X+4PHHH2fatGk88sgj5OTkkJOTQ21tLTabjZtvvpmsrCwikQhr1qxh1qxZfPzxx/ozfiQS4dxzz2X16tXcdtttnHnmmUQiET777DNqa2uTnkUhdt6uu+463nvvPd5++23OPvvslPdxwAOzQ2HXrl0Eg8E+h3wnT57MO++8QygUwul06j/USZMmGY4rLi4mPz9fLwfYtGkTs2bN6tMmwObNmw8amG3evJlhw4YZAsZwOMy2bdsAyMnJYejQoYY6VVVVuuObMmWKoaytrY36+noAhg4dSk7OVxkzVFXV25+RkaE/tD366KP6DXjZsmWcfvrpTJgwAavVSm1tLWPHjgXgwgsv5L/+678oKSnRp37eeOONfPLJJ0DswSMtLU3PDPSHP/yB733vewgh+OUvf8mcOXMYO3YsTqeTzs5OXeMzzjiDpUuXUlBQQHFxMRALVv72t78B8NFHH5GXl6cHxGvXrtUfju68807sdjsjR47Ub/7//u//jqqqTJgwgfHjx5Obm6tnufnTn/7Eb3/7WwBOOOEEhg8frp+v6upqFi1aBMRuoh6Ph2HDhukPzY899hhNTU0UFxczZ84cMjMz9ZvMO++8oy/0HD58ONOmTWPixIlYLBZaWlp0u1deeSXl5eUMGTJED2iWL1/O5s2bcblczJs3D7fbrTuxpqYmfR712rVrycrKoqKiAofDQSQSYe3atQBkZmZSWVlJYWEhRUWxNXcbNmzggw8+AKCyspLs7GwqKiqA2M35r3/9KwBTp06lpKSEUaNGkZaWhqZp+gPktGnTuPzyy8nLy6O0tBSILaSNO+jLL7+coUOHMnHiRL29r7zyit6m8vJyhg8frj9QPv/88/h8PoYPH84ll1xCVlaWfiN4++239Qem8ePHM378eCZNmoTZbKa+vp6HH34YgGuvvZYhQ4ZQWlqqB9ZPPPEEO3fuJDs7m/PPP5/09HT94fi9995j4cKFAKSlpTFz5kzGjRuH3W6ns7NTv/YvvPBCRo8eTXFxsX4z/tOf/qQHUPFzE/89bNiwgcceewyI/U5tNhujR4/G7XajKIrel9NOO43Zs2fj8Xj0QGPt2rW6/uvXr6egoIAJEyYA0NzcrD+QTZkyhZEjR1JeXq77iNWrVxOJROju7qaystLgI3bv3q23d/369fT09Og+oqenhzVr1gAxH1VZWWnwEZs2baK+vp6CggIqKysNPqKpqUl/6KqsrMRut+s+QlVVqqurgViQUFlZafAR0WiUSCSCEILKykpcLpfuIxIDgV27dlFZWan7iMSyzs5OKisrDT4isTyuQ9xHJD4k19bWUllZqfuIxHo+n4/KykqDj0gs37x5Mz6fT/cRiWV79+6lsrLS4CPiU3kikQiVlZUGH5H4YLR9+3YcDofuIxJfaLW1tVFZWWnwEfFyVVWprKw0+IhI5KuEPHV1dVRWVuo+IvHBu6enJ8lHJD5UbtiwgfT0dN1H9NXXRB8Rx+/3U1lZafARieWbN2+mo6ND9xGJNDY2UllZafARcUKhEJWVlQYfkdimrVu3IoTQfUTiOW9qaqKystLgI/x+v+HcJPqIxBd/27dvJy8vT/cRTqeTgoICPXiqrKw0+Ii4hiaTicrKSpxOp+4jEs95/DqM+4jEsvi5SfQRieWbNm0iNzdX9xGJ7d2zZw+VlZW6jzCZTFgsFlRVxev1JvkIp9OJy+XCbDbrzxJxH2Gz2fSy9vb2JB+Rm5uLpmk4nc4kH2G323G73aiqyu7du0lLS9N9ROI12tramuQjel/fiT7C6XSSk5ODqqr6dRj3EUIIbLZYxtu4hok+In7+4uctPT1d9xHx6XVCCBoaGgw+AtD9raIoST4iPT2dnJwcNE1jy5YtdHR06D4iLy+P8vJyXC4XgUAgyUdMnDgRn89HYWFhko+wWCzY7XY0TdODsLiPsNls5ObmIoTQ+5roIzweD8FgkLS0tCQf4XQ69el4kUiEQCCg+1ifz6e/NFBVlUAggM1mw2azoaoqzc2xZGnhcJhAIBBLuLXvJW9nZ6de12QyEQgEcDgcWCwWgsGg4WVEIBDAarVit9sRQuh2g8EgoVAIi8Wi23W5XJSUlKBpGlarlUAggN1u13+DJSUl+u8jEAhgsVj06Y4mk4mSkhIURUFRFAKBgOGl9Lhx43jmmWdwOBykpaVht9uZNGkSTzzxBM3NzaiqSjQa5fvf/z5VVVU88cQTemD24osv8umnn/LMM89wzTXX6BrGX/TFvw9iPrC1tZVvfetbNDY28umnnzJixAgCgQBmszkpu2MkEkFRFHp6eggEAobpk71fdByMYyIwi78By83NTSqLX+idnZ0UFxfT3t6un7C+jk18m9be3r5fm4nfeyDic3sTEUIQjUb18r7qxMt7o2maXtbXW62+7Ca+YYlGo0SjUb1NiTfC+AWbeLNPtBP/IcRpbW3V7fh8PoPdxBtLJBJJsptYHg6HDf1NLItrldjX+P/HtUi0m9if3nYTife1Lw0hplNf5waSz0/vOc697cbL42WJdhPnbPc+N/G68X/37mvicb3b1FuvRLu9+9zbbu+6iTfdRGdiNpuT2utyufD5fHpZ7ze2+2tvIvH29nVu4tdDYt3ebd/fuYl/Z+LxfZUnfldvu/HPEufEx6+z/fW1d3sT3573dc4TF3v3vl4SH/B7240/sCW2N1FDu92u3/x6240/sPXVV6fTicfj0W+svfsaf9CP65D4+x06dChnnXUWkUiEzMzMJLuXX345qqpSVlaWZHfu3LmUlZXR1dVl8JkQC+zvuOMO/H4/o0aNMvTVZDKxaNEiVFXV6yXavfHGG5k1axbNzc1kZGQY7E6ZMoU//OEPeL1e0tPTkzSMvwjZs2dPkoYLFy7k9ttvp7q6GpvNlmS3tbWVzs5OmpqaiEajeL1e/aHryy+/RNM01q9fn2T3Jz/5Cbfeeis7d+7U/VZcw5KSEtavX09XVxddXV1JfV2yZAnt7e1UVVXpdRP1XblyJW1tbeTm5iZd33/+858JBoO6b0+0e/vtt3P11VdTW1uLy+Uy+IgTTjiBl156ia6uLvLz85Ou7+eee45wOExHR0eS3VtuuYWLL76YhoYGCgsLDe2dNGkSn3/+OV6vV7+nJJ6blStXomkaDQ0N+lqTpqYmLBYLd999N3feeSe1tbV6f+KUl5fT3NxMV1cXO3fuTGpTfMRg7dq1RKNRg8+YP38+t9xyCzU1Nbr+8b7m5ubS3d1NT08Pu3fvTrL76quvEolE2LJlCw6Hw9CmSy+9lNbWVlpaWuju7k7SsL6+HkVR9PYmXi+/+c1v+M1vfsPWrVvx+/0Gu2effTaBQICWlhZqa2uTNNy2bRuqqvZ5HS5evJjFixdTVVWlt6mtrQ2Ijbh6vV5aW1t1/XtraDKZWLduXZKPuO2227jtttuoqamhra3N0NehQ4cSiUTwer3s2LEjye7f//53IBaU9faHN9xwAzfccAN1dXX6by7e1/jofjAYZPPmzUl24zNrtmzZQiAQMNidNWsWu3fvpqmpibq6uiQNV61aRTQa1duUqOGyZctYtmwZO3bswOv1GuzOmDGD9vZ22tvbqa6u1u22tsYyPr/11lt4PB7WrFmTZHfIkCGUlZWpVh+5AAAgAElEQVQRDoeTnjlzcnL0AYS8vDyEEHq5xWLRy4qLi5OeVYuKivRyh8NhKE9PT9fL4s/Z8XKTyWSwazKZDBq5XC7db/S+tgE9aAsGgwa7ieXBYFBfG5fId7/7XQoLC/WXhfG///mf/+G5555j69athMNf7Zsbz3oJ8NZbb5GVlcV3vvOd/Y5Axj+vqqrilFNOITs7m1WrVlFcXKy/HOqrbmJb+ooJDodjIjCLc6Bpj4llh3rc4R7bF1ZrciIFk8mkO6a+pjhYrdb9pkY1m816WV97HPRl1+PxMGfOHEwmE4WFhfobKIiNrH3ve99DURRGjBiBzWYz3HguvfRSJkyYQHt7u+GNBsR+8CeddBKapukjCnG7TqeTH/zgBwgh8Hg8SXavv/56Zs6cSXt7O+np6Yb+nnrqqbz66qv4fD6Kioqw2WyGvr700ksoioLf70+y++///u9cddVVNDY2UlpaarA7ffp03n33Xbq6unA4HEl2X331VYLBII2NjdhsNkNf582bxznnnENjYyMjR4402C0vL+epp55CCEF+fn6S3ddee41IJEJVVVWS3fnz5zN//nzq6+v16RZxDeNvhbxerz5ikdjXv/3tb6iqyubNm5Oumeuuu47LLruMhoYG/Q1Z3K7NZqOmpoZAIEB9fX2Sho8++igLFy5k9+7dFBUVGYLH008/naqqKlpbWwmHwwa7EBu98vv91NXVJdm99dZb9TbFr7U448aN45133sHr9epvDxM1fO6559i4caOhD3GuueYapk+fTmNjI2PGjDGUFRUVsXLlSkKhEKqqJrXp2WefJRAIUFVVhd1uN9T99re/zbRp02hubiY7O9vQV4fDwerVq1FVlY6OjiS7L730EtFolB07dujXWpyLLrqIjo4O2tvb6erqStIwFAoZRtUTr5dnnnmGZ555xjCqHufMM89EURTDqHqihrt37zaMqifaffDBB3nwwQdZu3Zt0gLyUaNG0dLSQldXF3v27AGM12F8BPWf//wnQgiD3SuvvJIrr7ySvXv36tOu4nYzMzN5/fXX8fl87Nq1K8nuf/7nfwKxh6PeD3PTp0/Xz3n8rW1iX++9915CoRDbt29PsjtnzhzmzJnDjh07CAaDBu2Lioq4+uqr9QfM3nYrKipQFEW/sSf2NTc3l9zcXP2taCJWq5X8/HwsFos+3TNx2md8ild85CLRbvwhJhAIJPkIh8PB1KlT9+sj4m+CN2/ejLJvq4k4ZWVllJWV0dDQoE+ditu1Wq1ccskl+m+jt92ZM2cCsdGn+NvwRLvXXnstLS0tNDY2GuwCXH311UQiEX0qWWLdSZMmMWnSJHbt2pU0rS0jI4NTTjmF9vZ26urqAOO5mTZtmv4GHmIvBON+KD5i5Ha79/tCKPG+3Ne0xfgIZaKG8cQCaWlp+tS0eF/jCQYsFos+OpNoNz7C0tHRQTgcNpxzp9OJ0+k0vCxK1LCwsJBwOKwHRv3xHNGX3aamJv26mjJlCqqq6td+Yl/jx8dHwfqyG/f7vfvau719nZt4WV/9TbTbu68HO+fxvvb1rHeodo/03NTX1+v+L/4stT+78e9OJB74qqqq+634MeXl5fpvKR4EJdaPT5mNj/YkEg98+7KbkZGh240nF+lLw4Nlm4yXHU7deCCYWPfnP/859913H//2b//Gww8/rCcjWbBgAY2NjXpwGJ9ef6C9h+N2V61aRVtbG7/85S8Nszx6a9i7vX21+3ATyAyqDabb2trweDxJ6fK3b99ORUUFy5Yt45ZbbjHUufPOO/nlL3+pD+3ec889LF68GL/fn5SJxePxcO655+oPGsXFxcyaNUuf9hXnrbfe4uKLL+Zvf/sb5513nv75YN1gOv7mJvEGJTm6SI1Tj9Q49UiNU4/UuH+QOqceqXHqORSNvykbTN9www0sX768z7Wgb7/9NhdccAF/+ctfktZljh8/nmHDhrFy5UrD5yeeeCI+n49169YhhOC73/0uH374IV1d+9/yKHEfM6fTyaJFi3jkkUe44447DqkP35gNpkeOHInL5dLXSCSyceNGRo0apc/3jK972rhxo2Fhd1NTE21tbYZ58pMmTdqvTaDPOfWDkWHDhukpQiWpQWqceqTGqUdqnHqkxv2D1Dn1SI1Tj9T4yDGZTEkp+desWcO6desYM2aMPivoggsuYMWKFbzyyitJCY/6Ij76duedd+Lz+frcXzkVHBOBmdVq5Vvf+havv/46v/jFL/RpIbW1tbz//vv6lBiIzat3Op288MILhsDshRdewGQyGTI9XX755dxyyy188cUX+rGKovDSSy8xY8aMpAyGg5XEjHCS1CA1Tj1S49QjNU49UuP+QeqceqTGqUdqfORcfPHFLFmyhIcffpjTTjuNLVu28NBDD+lJh+LTQm+66SZeeuklbrrpJjZt2qQvD/j888+ZPn16UgZliK0BzsjI4NZbb8Xv9/PII4+kvD+DIjBbuXIlfr9fH+rbsmULy5cvB2KZ1txuNz/72c846aSTuPjii7n77rv1Dabz8/O5/fbbdVu5ubncf//9LFiwgNzcXH2D6QceeIB58+YZdhC/6aabWLZsGVdddRWLFy+moKCAJ598ku3bt+upYSUSiUQikUgkEsng44EHHiASifDkk0+yaNEiJk6cyPPPP89vf/tbPbkPxBJkvfPOOzz88MP84Q9/YMmSJWRmZjJt2rSk7TkSueWWW0hPT+emm27C5/Px5JNPpnTj8UGxxmz48OH6ovPeVFdX61Hv2rVr+clPfsLnn3+O1Wrl7LPPZsmSJX3uObN06VKWLVtGTU0NRUVF+j5mvRdkNjc3c9ddd/Hmm28SCASYOnUqDz30UNIeWDB415hJJBKJRCKRSI4/vilrzI4HjsYas0ERmB0rDNbALJ4+1WQy7TeTj+TIkBqnHqlx6pEapx6pcf8gdU49UuPUcygay8DsyIinsD9YlsijwTcm+YfkwMT36ZCZk1KH1Dj1SI1Tj9Q49UiN+wepc+qRGqceqXHqSdwqoHe29sGInIMnkUgkEolEIpFIJAOMHDE7DsjMzERRFDnVIIVIjVOP1Dj1SI1Tj9S4f5A6px6pceqRGqcei8Wy342hByNyjdlhMFjXmEkkEolEIpFIjj/kGrNjh6OxxkxGFBKJRCKRSCQSiUQywMjATCKRSCQSiUQikUgGGBmYSSQSiUQikUgkEskAI1cbHgfs3r1bXzw6YsSIgW7OcYnUOPVIjVOP1Dj1SI37B6lz6pEapx6pceoJh8N68g+HwzHQzTkoMjA7Dujp6dH3wZCkBqlx6pEapx6pceqRGvcPUufUIzVOPVLj1KOq6jGVlVFOZZRIJBKJRCKRSCT9ygsvvIDJZOrz74477gCgtLSUefPm6XV27tyJyWTipZde0j/75JNPeOCBB/B6vf3eh6ONHDE7Dpg4ceJAN+G4R2qceqTGqUdqnHqkxv2D1Dn1SI1Tj9Q4xvPPP09FRYXhs5KSEgD+8pe/kJWVdcD6n3zyCT/72c+YN28emZmZhjKXy3V0G5tiZGB2HGCxWAa6Ccc9UuPUIzVOPVLj1CM17h+kzqlHapx6pMYxJk6cyIknnthn2bRp047I9pFMYQwEArjd7iP6/sNFTmWUSCQSiUQikUgkg47eUxl7c//993PPPfcAUFZWpk+F/OSTT/Rjfv/733PKKafgdrvJyMhg7ty5VFZWGuxcd911ZGdnU1lZybnnnktGRgbnnXdeajp1AOSImUQikUgkEolEcowRiCgD3QTc9iMPJVRVRVGMfbFaD83uzTffTGdnJ08++SQrVqzA4/EAMGHCBAAefPBBHnjgAebNm8eCBQsIh8P84he/YObMmaxZs4axY8fqtkKhEJdeeik//vGPueeee1BV9Yj7drjIwOw4oLOzE03TMJvN5OTkDHRzjkukxqlHapx6pMapR2rcP0idU4/UOPUcqcbjf/q3FLTq8KhZfNER2zjllFOSPotGo4cUnJWWllJWVgbEpj2WlpZ+1baaGh588EHmz5/PkiVLdHvnnnsuo0aN4sEHH+Tll1/Wjw+Hwzz00EN873vfO9IufW1kYHYcUFtbq6dblc4zNUiNU4/UOPVIjVOP1Lh/kDqnHqlx6pEax/jtb3/LuHHjDJ8d6ojZgXj77bdRVZXvfOc7hvViLpeLWbNm8cEHHyTVueKKK474e48EGZhJJBKJRCKRSCTHGFsePH+gm3BUGDdu3H6TfxwJzc3NAJx22ml9ltvtdsO/MzMzSUtLO+rtOBxkYHYcMGTIEH0oXJIapMapR2qceqTGqUdq3D9InVOP1Dj1HKnGR2N91/FMfn4+AMuXL2fIkCFJo3C9MzYOhk2o5Rk9DohfeJLUITVOPVLj1CM1Tj1S4/5B6px6pMapR2p8dHA4HAAEg0HD53PnzsVisbBnzx6+/e1vD0TTDhsZmEkkEolEIpFIJJJjkkmTJgHwq1/9iuuuuw6bzUZFRQUjR45k4cKF3H333ezcuZPzzz+f7Oxsmpqa+PLLL8nKyuKnP/3pALfeiAzMJBKJRCKRSCQSyTHJnDlzuOuuu/jd737HU089xf9v796joirXP4B/x+Eyw03kYlxM0coLCtIFgY4CSgh5Kyx12fKelR0zaR0VyzTsqHi6HOO4zJamaYhimKgpHu9aqSRmJVZWKhySVBRRRwQEeX5/9GNynGEYlGFm4PtZi1W88757v/vh9WU/7L3fXVNTg6+++gq9e/fG7Nmz0aNHD6SmpiI9PR2VlZXw9fVFaGgoBg0aZOmu61GIiFi6E7aipqYGGo1Gp8zV1ZX3XxMRERFRo/v999+1y8GTdTP0s2po7sArZs3ADz/8oF1utWfPnpbuTrPEGJsfY2x+jLH5McZNg3E2P8bY/Bhj87tx4wZEBAqFQrtcvjXjpR4iIiIiIiIL4xWzZsDJyQnV1dWN8jI+MowxNj/G2PwYY/NjjJsG42x+jLH5Mcbm16pVK+0VM1vAZ8wagM+YEREREVFT4TNmtqMxnjFjRkFERERERGRhTMyIiIiIiIgsjIkZEREREZEVatWqFaqqqizdDapHVVVVozzaxKcNm4HCwkLtw6Pt27e3dHeaJcbY/Bhj82OMzY8xbhqMs/kxxuZnSow9PDxw7tw5eHl5Qa1W28wiFtaisrJS+/+Ojo6Nvn0RQXl5OS5dugRvb+973h4Ts2agtLRU+x4MTp7mwRibH2Nsfoyx+THGTYNxNj/G2PxMibFarYa/vz9KSkpQUlLSxD20fRqNRrsqo6urq1n24ejoCH9/fyiVynveFhMzIiIiIiIrpVQq0bZtW0t3wybd/hJvW1jdksvlN4C1LpdfWVmp/WuAOS7TEmPcFBhj82OMzY8xbhqMs/kxxubHGJufpWPcrJfLP3LkCOLi4uDq6goXFxf07dsXBw8eNFh39+7diIiIgJOTE7y8vDBu3DgUFxfr1auqqsLcuXMREBAAR0dHdO3aFYsXLzb3oTQqR0dHqFQq/qM2I8bY/Bhj82OMzY8xbhqMs/kxxubHGJufrcXYZhKz3NxcREZGory8HGlpaUhLS0NFRQViYmJw+PBhnboHDhzAk08+ifvuuw+bN29Gamoqdu/ejZiYGJ2HAAHg73//O1JSUjB58mTs2LEDCQkJmDp1KhYsWNCUh0dERERERC2YzdzKGB8fj++//x5nzpyBk5MTgD8f6OvUqRM6d+6sc+WsV69eKCsrww8//AA7uz8fozt06BD+9re/4cMPP8TLL78MAPjxxx8RFBSE+fPn4/XXX9e2f/HFF7FmzRqcPXsWHh4e2nJrvZWRiIiIiIisS0NzB5tZ/OPgwYMYOHCgNikD/jywyMhIbNy4EefOnYOvry+KioqQm5uLlJQUbVIGAI8//jg6d+6MrKwsbWK2adMmiAjGjx+vs6/x48dj+fLl+O9//4vnnntOW24oh62pqWnsQ22w23/g5lpxpqVjjM2PMTY/xtj8GOOmwTibH2Nsfoyx+Vk6xobyBGPXxGwmMbt586bB+0Nry/Ly8uDr64sTJ04AAIKDg/XqBgcH61xZO3HiBLy9veHj46NXr/bz2xkKZFlZWQOPxLzuzMqp8THG5scYmx9jbH6McdNgnM2PMTY/xtj8rCXGxhIzm7kHLzAwEDk5OTqZZ3V1Nb755hsA0L7bofa/t9+CWMvDw0PnHRAlJSUG6zk7O8PBwYHviyAiIiIioiZhM4nZlClT8Ouvv+KVV15BUVERfv/9d0yaNAn/+9//AEDvXs263ox+Z7mxN6jz7epERERERNQUbCYxmzBhAhYuXIi0tDS0a9cO7du3x08//YRp06YBAPz9/QEAnp6eAGDwatfly5d1rpB5enoarFdWVoabN28avJpGRERERETU2GzmGTMASEpKQmJiIn777Te4urqiQ4cOeOmll+Ds7IxHH30UANCjRw8Afz5zNmDAAJ32eXl52s8BICgoCBkZGTh//rzOc2Z5eXk626rVqlUrODs765QpFApeWSMiIiIiIh0iovdMmbHV3G1muXxDCgsLERwcjPHjx2PRokXa8rCwMNy4cQPff/89lEolACAnJwcRERFYunQpJk2aBOCv5fJTUlKQlJSkbT9p0iR8+umnesvlExERERERmYMyOTk52dKdMMWJEyewdOlSlJWVobCwEFlZWRgzZgweeOABrF69Gg4ODtq6Dz30EBYtWoQffvgBnp6eyMnJwUsvvYT27dtj6dKl2mX027Zti7NnzyI1NRUqlQpVVVVYvnw5UlNTkZycjP79+1vqcImIiIiIqAWxmWfMHBwcsHfvXowZMwYDBw7ERx99hEmTJmH//v1wcXHRqRsdHY3s7GycO3cOgwcPxpQpU9C3b1/s2bNHb8n9Dz/8EDNnzsTixYvRv39/bNiwAampqXjjjTea8vD0XL9+HYmJifDz84NKpUJISAgyMjJMaltcXIxx48bBy8sLTk5OiIiIwJ49e8zcY9uzd+9eTJgwAV27doWzszP8/f3x1FNP4dtvv6237apVq7S3sd75df78+SbovW3Yv39/nXHKycmpt/2ZM2cwdOhQuLu7w8XFBbGxsTh27FgT9Nx2jBs3rs4Y1xdnjmPDNBoNZsyYgf79+8Pb2xsKhQJ1/Q3z2LFjeOKJJ+Di4gJ3d3cMHToUZ86cMXlfu3fvRkREBJycnODl5YVx48ahuLi4kY7EepkS41u3buHf//434uPj0a5dOzg5OaFbt26YOXMmrly5YtJ+oqOjDY7v+Ph4MxyVdTF1HNc1h3Tt2tXkfWVkZCAkJAQqlQp+fn5ITEzE9evXG/ForJOpMTY2R5sS55Y8jhtyrtYc5mObecasc+fOOHDggMn1Y2NjERsbW289e3t7JCcn1/lL11KGDh2K3NxcLFy4EJ07d8batWsxcuRI1NTU6Lz0+k6VlZWIiYnBlStXkJqairZt22LJkiWIj4/H7t27ERUV1YRHYd2WLl2KkpISTJ06FYGBgbh48SLef/99hIeHY8eOHejXr1+92/jkk0/0JtXaBWjoLwsWLEDfvn11yu58hvNOFy9eRJ8+fdCmTRusXLkSKpUKKSkpiI6ORm5uLrp06WLOLtuM2bNna2/Pvt3gwYPh6OiI0NDQerfBcayrpKQEy5YtQ8+ePfH000/j448/Nljv5MmTiI6ORkhICD777DNUVFRgzpw56NOnD77//nt4e3sb3c+BAwfw5JNPYuDAgdi8eTOKi4uRlJSEmJgYHD161OC7O5sLU2JcXl6O5ORkjBw5EhMnToSXlxeOHTuGefPm4YsvvsDRo0ehVqvr3VenTp2Qnp6uU+bu7t5ox2KtTB3HAKBWq7F37169MlOkp6dj1KhRmDhxIhYtWoRff/0VSUlJ+Omnn7Bz5857OgZrZ2qMDx8+rFf2zTffIDExEQkJCSbtq6WOY1PP1ZrNfCxkdbZt2yYAZO3atTrlsbGx4ufnJ9XV1XW2XbJkiQCQQ4cOacuqqqokMDBQevXqZbY+26ILFy7olWk0GrnvvvskJibGaNtPPvlEAEhubq65utcs7Nu3TwBIZmZmg9tOnz5d7O3tpaCgQFt29epV8fLykuHDhzdmN5ud/fv3CwB58803jdbjODaspqZGampqRETk4sWLAkDeeustvXrDhg0TLy8vuXr1qrasoKBA7O3tZcaMGfXuJzQ0VAIDA6WqqkpbdvDgQQEgH3744b0fiBUzJcbV1dVy6dIlvbaZmZkCQNLS0urdT1RUlHTv3r1R+mxrTB3HY8eOFWdn57vaR3V1tfj6+kr//v11ytPT0wWAZGdn39V2bYWpMTZk3LhxolAo5Lfffqu3bksex6aeqzWX+dhmbmVsSbKysuDi4oJhw4bplI8fPx5//PGH9qXadbXt0qULIiIitGV2dnYYNWoUjhw5gqKiIrP129a0bdtWr8zFxQWBgYH4/fffLdAjul1WVhb69euHDh06aMvc3NwwdOhQfPHFF6iurrZg76zbihUroFAoMGHCBEt3xSaZstpudXU1tm7dimeeeQZubm7a8g4dOqBv377Iysoy2r6oqAi5ubkYPXq09rlnAHj88cfRuXPnetvbOlNirFQqDV657dWrFwBwnq5HU6wanZOTg3PnzmH8+PE65cOGDYOLiwvHcR00Gg0yMzMRFRWFBx980Aw9az5MOVdrTvMxEzMrdOLECXTr1k1ncABAcHCw9nNjbWvrGWr7448/NmJPm5+rV6/i2LFj6N69u0n1Bw0aBKVSCQ8PDwwdOtToz6Ylmzx5Muzs7ODm5oa4uDh8/fXXRuuXl5fj9OnTdY7l8vLyBt033pJcvXoVGzZsQExMDDp27GhSG47jhjt9+jTKy8vrHKOnTp1CRUVFne1rY1xXe/4M6lZ7y52p8/Tp06fh4eEBOzs7PPDAA5g1axbKy8vN2UWbU15eDh8fHyiVSrRr1w6vvPIKLl++XG+7usaxvb09unbtynFch4yMDJSVlWHixIkmt+E4/sud52rNaT62mWfMWpKSkhJ06tRJr7x26X5DL8W+va2hJf5NaUt/JhBlZWWYNWuW0Xo+Pj6YNWsWwsPD4ebmhry8PCxcuBDh4eE4ePAgevbs2UQ9tm6tW7fG1KlTER0dDU9PT5w6dQrvvvsuoqOjsW3bNsTFxRlsV1paChHhWL4L69atQ3l5OZ5//vl663Ic373a8VfXGBURlJaWwtfX967ac3wbVlRUhJkzZ+Kxxx7DoEGD6q3fu3dvjBgxAl27dkV5eTm2b9+Od955B19//TX27dtn9H1CLUXPnj3Rs2dP7XO/Bw4cwKJFi7Bnzx7k5ubqLbB2u/rGcUFBgVn6bOtWrFgBd3d3PPPMMybV5zjWdee5WnOaj5mYWSljl8bru2x+L21bstmzZyM9PR2LFy/WvrC8LvHx8TqrIUVGRmLgwIEICgrCnDlzsHnzZnN31yY8/PDDePjhh7Xf9+nTBwkJCQgKCsKMGTPqTMxqcSw33IoVK+Dp6WnSA+Ucx/fuXsdoXXU4vvVdvnwZAwYMgIhg/fr1Jp2Mzps3T+f7AQMGICAgANOmTcPmzZtNXnihOXvttdd0vo+NjcXDDz+MZ599FsuXL9f73BCOY9P9+OOP+OabbzB58mSoVCqT2nAc/8XYuVpzmI9bVoptIzw9PQ1m57W3FRh76fW9tG3J5s6di3nz5mH+/Pl45ZVX7mobAQEB6N27t0nLwLdk7u7uGDRoEI4fP17nbRht2rSBQqHgWG6g48eP4+jRoxg1atRdryDFcWya2mef6hqjCoXC6Ipp9bXn+NZVWlqK2NhYFBUVYdeuXQbvKjHVqFGjAIBj3IiEhAQ4OzvXGyOO44ZbsWIFADToNkZDWuI4rutcrTnNx0zMrFBQUBB+/vlnvcUN8vLyABhfZjwoKEhbr6FtW6q5c+dqX5lwr++vE5EWd0vB3RARAHX/FUqtVuPBBx+scyyr1ep7OjFrrhrrFz7Hcf0eeOABqNXqOsfogw8+aPSv4bVzcV3tOVf/pbS0FE888QTy8/Oxa9cug8+B3A2OceNMmQeCgoIA6I/j6upqnDx5kuP4Djdv3kRaWhoeffRRhISENMo2W8o4Nnau1pzm45bx07QxCQkJuH79Oj7//HOd8tWrV8PPzw9hYWFG2548eVJn5cbq6mqsWbMGYWFh8PPzM1u/bdE///lPJCcn480338Rbb711T9vKz8/HwYMHER4e3ki9a55KS0uxdetW7ctI65KQkIC9e/fqrLym0WiwceNGDBkyRG9xnJausrISa9asQa9eve7plwjHsWns7OwwePBgbNy4ERqNRlteWFiIffv2YejQoUbb+/v7o1evXlizZg1u3bqlLc/JycEvv/xSb/uWojYpO3PmDHbu3Klza/TdWr16NQBwjBuxYcMG3Lhxo94YhYWFwdfXF6tWrdJrf/36dY7jO2zZsgWXLl0y6Rng+rSkcVzfuVqzmo+bbGF+apDY2Fhp06aNLFu2TPbu3SsvvPCCAJA1a9Zo60yYMEGUSqXOe54qKiqke/fucv/990t6errs2rVLEhISxM7OTvbv32+JQ7Fa7733ngCQ+Ph4OXz4sN5XLUNxjomJkblz50pWVpbs2bNHPvjgA/Hz8xNXV1fJy8uzxOFYpZEjR0pSUpJkZmbKvn37ZNmyZdKlSxexs7OTXbt2aev169dPlEqlTtvi4mLx9fWVoKAgycrKkuzsbImMjBRXV1f5+eefm/pQrF5GRoYAkGXLlhn8nOO4YbKzsyUzM1NWrlwpAGTYsGGSmZkpmZmZUlZWJiIiP//8s7i4uEhkZKRkZ2fLxo0bpUePHuLn5yfFxcU621MqldKvXz+dsn379omdnZ0kJCTIrl27JD09Xe6//37p0aOHVFRUNNmxWkp9Mb5x44aEhoaKQqGQ1NRUvTn61KlTOtu7M8ZffvmlxMXFyUcffSQ7d+6ULVu2yLHAIu0AAAldSURBVMsvv6ytd+vWraY+5CZXX4wLCgrk8ccfl//85z+SnZ0t27dvl5kzZ4pKpZLu3bvL9evXtdsqKCgQpVIpEyZM0NlHWlqaAJAXX3xRO8+7u7tLbGxsUx+uRZgyV9SKj48XtVotV65cqXN7HMe6TD1Xay7zMRMzK6XRaOTVV18VHx8fcXBwkODgYFm3bp1OnbFjxwoAyc/P1yk/f/68jBkzRjw8PESlUkl4eLjOSTD9KSoqSgDU+VXLUJwTExMlMDBQXF1dxc7OTvz8/GTUqFHyyy+/WOBIrFdKSoqEhIRI69atRalUire3tyQkJMiRI0d06tX+LO506tQpefrpp8XNzU2cnJwkJiZGvv3226bqvk2JjY0VZ2dnuXbtmsHPOY4bpkOHDnXODbfH8OjRoxITEyNOTk7i5uYmTz/9tF7CICICQKKiovTKd+7cKeHh4aJSqcTDw0PGjBlj8IWqzVF9Mc7Pzzc6R48dO1Zne3fG+LfffpMBAwaIv7+/ODo6ikqlkqCgIJk/f36LSHxF6o/x5cuXJSEhQQICAkStVouDg4M89NBDMmPGDL3kofbncWfcRUTWrl0rwcHB4uDgID4+PvLqq6+KRqNpoqO0LFPnisLCQmnVqpWMGTPG6PY4jnWZeq4m0jzmY8X/d5CIiIiIiIgshM+YERERERERWRgTMyIiIiIiIgtjYkZERERERGRhTMyIiIiIiIgsjIkZERERERGRhTExIyIiIiIisjAmZkRERERERBbGxIyIiIiIiMjCmJgREZFNOHToEJKTk3HlyhW9z6KjoxEdHd30narHp59+Cm9vb2g0Gov1ITIyEomJiRbbPxERmUYhImLpThAREdXnvffew/Tp05Gfn4+AgACdz3766ScAQGBgoAV6ZtiNGzfQuXNnJCYmYtq0aRbrx4EDBxAbG4u8vDx06dLFYv0gIiLjeMWMiIhsXmBgoFUlZQCwevVqlJSUYOLEiRbtR1RUFLp06YL333/fov0gIiLjmJgREZHVS05OxvTp0wEAHTt2hEKhgEKhwP79+wHo38pYUFAAhUKBd999F//6178QEBAAtVqN6Oho/Prrr6iqqsLMmTPh5+eH1q1bIyEhAcXFxXr7Xb9+PSIiIuDs7AwXFxfExcXhu+++M6nPS5cuxeDBg+Hu7q5TnpmZibCwMLRu3RpOTk7o1KkTJkyYoFPn2rVrmDZtGjp27AgHBwf4+/sjMTERZWVlOvVqamqwePFihISEQK1Ww93dHeHh4diyZYtOvdGjR2Pt2rUWvaWSiIiMY2JGRERWb+LEiZgyZQoAYOPGjTh8+DAOHz6MRx55xGi7JUuW4ODBg1iyZAk+/vhjnDx5EoMHD8bzzz+PixcvYuXKlXjnnXewe/duvStbCxYswMiRIxEYGIjPPvsMaWlp0Gg06NOnj/bWybqcPXsWeXl56Nu3r0754cOHMWLECHTq1AkZGRnYtm0b5syZg+rqam2dGzduICoqCqtXr8arr76K7du3IykpCatWrcKQIUNw+xMI48aNw9SpUxEaGor169cjIyMDQ4YMQUFBgc5+o6OjUVZWpk1kiYjICgkREZENePfddwWA5Ofn630WFRUlUVFR2u/z8/MFgPTs2VNu3bqlLf/ggw8EgAwZMkSnfWJiogCQq1eviohIYWGh2NnZyZQpU3TqaTQa8fHxkeHDhxvt6/r16wWA5OTk6JS/9957AkCuXLlSZ9uUlBRp1aqV5Obm6pRv2LBBAEh2draIiHz55ZcCQGbNmmW0LyIiN2/eFIVCIUlJSfXWJSIiy+AVMyIiarYGDBiAVq3++lXXrVs3AMDAgQN16tWWFxYWAgB27NiB6upqjBkzBtXV1dovlUqFqKioeq88/fHHHwCAtm3b6pSHhoYCAIYPH47PPvsMRUVFem23bt2KHj16ICQkRGffcXFxOrdvbt++HQAwefLkeuNgb28Pd3d3g/sjIiLrwMSMiIiaLQ8PD53vHRwcjJZXVFQAAC5cuADgz0TK3t5e52v9+vW4dOmS0f2Wl5cDAFQqlU55ZGQkNm3apE362rVrhx49emDdunXaOhcuXMDx48f19uvq6goR0e774sWLUCqV8PHxMSkWKpVK2y8iIrI+dpbuABERkbXx8vICAGzYsAEdOnS46/aXL1+Gr6+vzmdPPfUUnnrqKVRWViInJwcpKSl47rnnEBAQgIiICHh5eUGtVmPlypVGt+3t7Y1bt27h/PnzevswpLS0VNuWiIisDxMzIiKyCY6OjgDQJFd94uLiYGdnh9OnT+OZZ55pcPuuXbsCAE6fPo3u3bsbrOPo6IioqCi4u7tjx44d+O677xAREYFBgwZhwYIF8PT0RMeOHevcx5NPPomUlBQsXboUb7/9ttH+/PHHH6ioqLC6VwoQEdFfmJgREZFNCAoKAgCkpqZi7NixsLe3R5cuXeDq6tro+woICMDbb7+NWbNm4cyZM4iPj0ebNm1w4cIFHDlyBM7Ozpg7d26d7cPCwqBWq5GTk4MhQ4Zoy+fMmYOzZ88iJiYG7dq1w5UrV5Camgp7e3tERUUBABITE/H5558jMjISr732GoKDg1FTU4PCwkLs3LkT//jHPxAWFoY+ffpg9OjRmDdvHi5cuIBBgwbB0dER3333HZycnLSrWAJATk4OAOitEklERNaDiRkREdmE6OhovP7661i9ejWWL1+Ompoa7Nu3T+f9ZY3p9ddfR2BgIFJTU7Fu3TpUVlbCx8cHoaGhmDRpktG2Dg4OePbZZ7F582YsWLBAWx4WFoajR48iKSkJFy9ehLu7Ox577DHs3btXe2XN2dkZX331FRYuXIhly5YhPz8farUa7du3xxNPPIGAgADt9latWoVHHnkEK1aswKpVq6BWqxEYGIg33nhDpz+bNm1CUFCQNrklIiLroxC57YUoRERE1CiOHj2K0NBQ5OTkICwszGL9uHbtGvz8/LBo0SK88MILFusHEREZx8SMiIjITEaMGIGysjJs3brVYn2YO3cu1q9fj+PHj8POjjfKEBFZKy6XT0REZCbvv/8+QkNDodFoLNYHNzc3rFq1ikkZEZGV4xUzIiIiIiIiC+MVMyIiIiIiIgtjYkZERERERGRhTMyIiIiIiIgsjIkZERERERGRhTExIyIiIiIisjAmZkRERERERBbGxIyIiIiIiMjCmJgRERERERFZ2P8BJNkAU5/850UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from filterpy.common import Q_discrete_white_noise\n",
    "from filterpy.kalman import ExtendedKalmanFilter\n",
    "from numpy import eye, array, asarray\n",
    "import numpy as np\n",
    "\n",
    "dt = 0.05\n",
    "rk = ExtendedKalmanFilter(dim_x=3, dim_z=1)\n",
    "radar = RadarSim(dt, pos=0., vel=100., alt=1000.)\n",
    "\n",
    "# make an imperfect starting guess\n",
    "rk.x = array([radar.pos-100, radar.vel+100, radar.alt+1000])\n",
    "\n",
    "rk.F = eye(3) + array([[0, 1, 0],\n",
    "                       [0, 0, 0],\n",
    "                       [0, 0, 0]]) * dt\n",
    "\n",
    "range_std = 5. # meters\n",
    "rk.R = np.diag([range_std**2])\n",
    "rk.Q[0:2, 0:2] = Q_discrete_white_noise(2, dt=dt, var=0.1)\n",
    "rk.Q[2,2] = 0.1\n",
    "rk.P *= 50\n",
    "\n",
    "xs, track = [], []\n",
    "for i in range(int(20/dt)):\n",
    "    z = radar.get_range()\n",
    "    track.append((radar.pos, radar.vel, radar.alt))\n",
    "    \n",
    "    rk.update(array([z]), HJacobian_at, hx)\n",
    "    xs.append(rk.x)\n",
    "    rk.predict()\n",
    "\n",
    "xs = asarray(xs)\n",
    "track = asarray(track)\n",
    "time = np.arange(0, len(xs)*dt, dt)\n",
    "ekf_internal.plot_radar(xs, track, time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using SymPy to compute Jacobians\n",
    "\n",
    "Depending on your experience with derivatives you may have found the computation of the Jacobian difficult. Even if you found it easy, a slightly more difficult problem easily leads to very difficult computations.\n",
    "\n",
    "As explained in Appendix A, we can use the SymPy package to compute the Jacobian for us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$$\\left[\\begin{matrix}\\frac{x}{\\sqrt{x^{2} + y^{2}}} & 0 & \\frac{y}{\\sqrt{x^{2} + y^{2}}}\\end{matrix}\\right]$$"
      ],
      "text/plain": [
       "⎡     x                y      ⎤\n",
       "⎢────────────  0  ────────────⎥\n",
       "⎢   _________        _________⎥\n",
       "⎢  ╱  2    2        ╱  2    2 ⎥\n",
       "⎣╲╱  x  + y       ╲╱  x  + y  ⎦"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sympy\n",
    "sympy.init_printing(use_latex=True)\n",
    "\n",
    "x, x_vel, y = sympy.symbols('x, x_vel y')\n",
    "\n",
    "H = sympy.Matrix([sympy.sqrt(x**2 + y**2)])\n",
    "\n",
    "state = sympy.Matrix([x, x_vel, y])\n",
    "H.jacobian(state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This result is the same as the result we computed above, and with much less effort on our part!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Robot Localization\n",
    "\n",
    "It's time to try a real problem. I warn you that this section is difficult. However, most books choose simple, textbook problems with simple answers, and you are left wondering how to solve a real world problem. \n",
    "\n",
    "We will consider the problem of robot localization. We already implemented this in the **Unscented Kalman Filter** chapter, and I recommend you read it now if you haven't already.  In this scenario we have a robot that is moving through a landscape using a sensor to detect landmarks. This could be a self driving car using computer vision to identify trees, buildings, and other landmarks. It might be one of those small robots that vacuum your house, or a robot in a warehouse.\n",
    "\n",
    "The robot has 4 wheels in the same configuration used by automobiles. It maneuvers by pivoting the front wheels. This causes the robot to pivot around the rear axle while moving forward. This is nonlinear behavior which we will have to model. \n",
    "\n",
    "The robot has a sensor that measures the range and bearing to known targets in the landscape. This is nonlinear because computing a position from a range and bearing requires square roots and trigonometry. \n",
    "\n",
    "Both the process model and measurement models are nonlinear. The EKF accommodates both, so we provisionally conclude that the EKF is a viable choice for this problem."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Robot Motion Model\n",
    "\n",
    "At a first approximation an automobile steers by pivoting the front tires while moving forward. The front of the car moves in the direction that the wheels are pointing while pivoting around the rear tires. This simple description is complicated by issues such as slippage due to friction, the differing behavior of the rubber tires at different speeds, and the need for the outside tire to travel a different radius than the inner tire. Accurately modeling steering requires a complicated set of differential equations. \n",
    "\n",
    "For lower speed robotic applications a simpler *bicycle model* has been found to perform well. This is a depiction of the model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ekf_internal.plot_bicycle()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the **Unscented Kalman Filter** chapter we derived these equations:\n",
    "\n",
    "$$\\begin{aligned} \n",
    "\\beta &= \\frac d w \\tan(\\alpha) \\\\\n",
    "x &= x - R\\sin(\\theta) + R\\sin(\\theta + \\beta) \\\\\n",
    "y &= y + R\\cos(\\theta) - R\\cos(\\theta + \\beta) \\\\\n",
    "\\theta &= \\theta + \\beta\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "where $\\theta$ is the robot's heading.\n",
    "\n",
    "You do not need to understand this model in detail if you are not interested in steering models. The important thing to recognize is that our motion model is nonlinear, and we will need to deal with that with our Kalman filter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the State Variables\n",
    "\n",
    "For our filter we will maintain the position $x,y$ and orientation $\\theta$ of the robot:\n",
    "\n",
    "$$\\mathbf x = \\begin{bmatrix}x \\\\ y \\\\ \\theta\\end{bmatrix}$$\n",
    "\n",
    "Our control input $\\mathbf u$ is the velocity $v$ and steering angle $\\alpha$:\n",
    "\n",
    "$$\\mathbf u = \\begin{bmatrix}v \\\\ \\alpha\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the System Model\n",
    "\n",
    "We model our system as a nonlinear motion model plus noise.\n",
    "\n",
    "$$\\bar x = f(x, u) + \\mathcal{N}(0, Q)$$\n",
    "\n",
    "\n",
    "\n",
    "Using the motion model for a robot that we created above, we can expand this to\n",
    "\n",
    "$$\\bar{\\begin{bmatrix}x\\\\y\\\\\\theta\\end{bmatrix}} = \\begin{bmatrix}x\\\\y\\\\\\theta\\end{bmatrix} + \n",
    "\\begin{bmatrix}- R\\sin(\\theta) + R\\sin(\\theta + \\beta) \\\\\n",
    "R\\cos(\\theta) - R\\cos(\\theta + \\beta) \\\\\n",
    "\\beta\\end{bmatrix}$$\n",
    "\n",
    "We find The $\\mathbf F$ by taking the Jacobian of $f(x,u)$.\n",
    "\n",
    "$$\\mathbf F = \\frac{\\partial f(x, u)}{\\partial x} =\\begin{bmatrix}\n",
    "\\frac{\\partial f_1}{\\partial x} & \n",
    "\\frac{\\partial f_1}{\\partial y} &\n",
    "\\frac{\\partial f_1}{\\partial \\theta}\\\\\n",
    "\\frac{\\partial f_2}{\\partial x} & \n",
    "\\frac{\\partial f_2}{\\partial y} &\n",
    "\\frac{\\partial f_2}{\\partial \\theta} \\\\\n",
    "\\frac{\\partial f_3}{\\partial x} & \n",
    "\\frac{\\partial f_3}{\\partial y} &\n",
    "\\frac{\\partial f_3}{\\partial \\theta}\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "\n",
    "When we calculate these we get\n",
    "\n",
    "$$\\mathbf F = \\begin{bmatrix}\n",
    "1 & 0 & -R\\cos(\\theta) + R\\cos(\\theta+\\beta) \\\\\n",
    "0 & 1 & -R\\sin(\\theta) + R\\sin(\\theta+\\beta) \\\\\n",
    "0 & 0 & 1\n",
    "\\end{bmatrix}$$\n",
    "\n",
    "We can double check our work with SymPy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$\\left[\\begin{matrix}1 & 0 & - \\frac{w \\cos{\\left (\\theta \\right )}}{\\tan{\\left (\\alpha \\right )}} + \\frac{w}{\\tan{\\left (\\alpha \\right )}} \\cos{\\left (\\frac{t v}{w} \\tan{\\left (\\alpha \\right )} + \\theta \\right )}\\\\0 & 1 & - \\frac{w \\sin{\\left (\\theta \\right )}}{\\tan{\\left (\\alpha \\right )}} + \\frac{w}{\\tan{\\left (\\alpha \\right )}} \\sin{\\left (\\frac{t v}{w} \\tan{\\left (\\alpha \\right )} + \\theta \\right )}\\\\0 & 0 & 1\\end{matrix}\\right]$$"
      ],
      "text/plain": [
       "⎡                        ⎛t⋅v⋅tan(α)    ⎞⎤\n",
       "⎢                   w⋅cos⎜────────── + θ⎟⎥\n",
       "⎢        w⋅cos(θ)        ⎝    w         ⎠⎥\n",
       "⎢1  0  - ──────── + ─────────────────────⎥\n",
       "⎢         tan(α)            tan(α)       ⎥\n",
       "⎢                                        ⎥\n",
       "⎢                        ⎛t⋅v⋅tan(α)    ⎞⎥\n",
       "⎢                   w⋅sin⎜────────── + θ⎟⎥\n",
       "⎢        w⋅sin(θ)        ⎝    w         ⎠⎥\n",
       "⎢0  1  - ──────── + ─────────────────────⎥\n",
       "⎢         tan(α)            tan(α)       ⎥\n",
       "⎢                                        ⎥\n",
       "⎣0  0                  1                 ⎦"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sympy\n",
    "from sympy.abc import alpha, x, y, v, w, R, theta\n",
    "from sympy import symbols, Matrix\n",
    "sympy.init_printing(use_latex=\"mathjax\", fontsize='16pt')\n",
    "time = symbols('t')\n",
    "d = v*time\n",
    "beta = (d/w)*sympy.tan(alpha)\n",
    "r = w/sympy.tan(alpha)\n",
    "\n",
    "fxu = Matrix([[x-r*sympy.sin(theta) + r*sympy.sin(theta+beta)],\n",
    "              [y+r*sympy.cos(theta)- r*sympy.cos(theta+beta)],\n",
    "              [theta+beta]])\n",
    "F = fxu.jacobian(Matrix([x, y, theta]))\n",
    "F"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That looks a bit complicated. We can use SymPy to substitute terms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$\\left[\\begin{matrix}1 & 0 & - R \\cos{\\left (\\theta \\right )} + R \\cos{\\left (\\beta + \\theta \\right )}\\\\0 & 1 & - R \\sin{\\left (\\theta \\right )} + R \\sin{\\left (\\beta + \\theta \\right )}\\\\0 & 0 & 1\\end{matrix}\\right]$$"
      ],
      "text/plain": [
       "⎡1  0  -R⋅cos(θ) + R⋅cos(β + θ)⎤\n",
       "⎢                              ⎥\n",
       "⎢0  1  -R⋅sin(θ) + R⋅sin(β + θ)⎥\n",
       "⎢                              ⎥\n",
       "⎣0  0             1            ⎦"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reduce common expressions\n",
    "B, R = symbols('beta, R')\n",
    "F = F.subs((d/w)*sympy.tan(alpha), B)\n",
    "F.subs(w/sympy.tan(alpha), R)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This form  verifies that the computation of the Jacobian is correct.\n",
    "\n",
    "Now we can turn our attention to the noise. Here, the noise is in our control input, so it is in *control space*. In other words, we command a specific velocity and steering angle, but we need to convert that into errors in $x, y, \\theta$. In a real system this might vary depending on velocity, so it will need to be recomputed for every prediction. I will choose this as the noise model; for a real robot you will need to choose a model that accurately depicts the error in your system. \n",
    "\n",
    "$$\\mathbf{M} = \\begin{bmatrix}\\sigma_{vel}^2 & 0 \\\\ 0 & \\sigma_\\alpha^2\\end{bmatrix}$$\n",
    "\n",
    "If this was a linear problem we would convert from control space to state space using the by now familiar $\\mathbf{FMF}^\\mathsf T$ form. Since our motion model is nonlinear we do not try to find a closed form solution to this, but instead linearize it with a Jacobian which we will name $\\mathbf{V}$. \n",
    "\n",
    "$$\\mathbf{V} = \\frac{\\partial f(x, u)}{\\partial u} \\begin{bmatrix}\n",
    "\\frac{\\partial f_1}{\\partial v} & \\frac{\\partial f_1}{\\partial \\alpha} \\\\\n",
    "\\frac{\\partial f_2}{\\partial v} & \\frac{\\partial f_2}{\\partial \\alpha} \\\\\n",
    "\\frac{\\partial f_3}{\\partial v} & \\frac{\\partial f_3}{\\partial \\alpha}\n",
    "\\end{bmatrix}$$\n",
    "\n",
    "These partial derivatives become very difficult to work with. Let's compute them with SymPy. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$\\left[\\begin{matrix}t \\cos{\\left (\\beta + \\theta \\right )} & \\frac{d \\cos{\\left (\\beta + \\theta \\right )}}{\\tan{\\left (\\alpha \\right )}} \\left(\\tan^{2}{\\left (\\alpha \\right )} + 1\\right) - \\frac{w \\sin{\\left (\\theta \\right )}}{\\tan^{2}{\\left (\\alpha \\right )}} \\left(- \\tan^{2}{\\left (\\alpha \\right )} - 1\\right) + \\frac{w \\sin{\\left (\\beta + \\theta \\right )}}{\\tan^{2}{\\left (\\alpha \\right )}} \\left(- \\tan^{2}{\\left (\\alpha \\right )} - 1\\right)\\\\t \\sin{\\left (\\beta + \\theta \\right )} & \\frac{d \\sin{\\left (\\beta + \\theta \\right )}}{\\tan{\\left (\\alpha \\right )}} \\left(\\tan^{2}{\\left (\\alpha \\right )} + 1\\right) + \\frac{w \\cos{\\left (\\theta \\right )}}{\\tan^{2}{\\left (\\alpha \\right )}} \\left(- \\tan^{2}{\\left (\\alpha \\right )} - 1\\right) - \\frac{w \\cos{\\left (\\beta + \\theta \\right )}}{\\tan^{2}{\\left (\\alpha \\right )}} \\left(- \\tan^{2}{\\left (\\alpha \\right )} - 1\\right)\\\\\\frac{t}{R} & \\frac{d}{w} \\left(\\tan^{2}{\\left (\\alpha \\right )} + 1\\right)\\end{matrix}\\right]$$"
      ],
      "text/plain": [
       "⎡                ⎛   2       ⎞                ⎛     2       ⎞            ⎛    \n",
       "⎢              d⋅⎝tan (α) + 1⎠⋅cos(β + θ)   w⋅⎝- tan (α) - 1⎠⋅sin(θ)   w⋅⎝- ta\n",
       "⎢t⋅cos(β + θ)  ────────────────────────── - ──────────────────────── + ───────\n",
       "⎢                        tan(α)                        2                      \n",
       "⎢                                                   tan (α)                   \n",
       "⎢                                                                             \n",
       "⎢                ⎛   2       ⎞                ⎛     2       ⎞            ⎛    \n",
       "⎢              d⋅⎝tan (α) + 1⎠⋅sin(β + θ)   w⋅⎝- tan (α) - 1⎠⋅cos(θ)   w⋅⎝- ta\n",
       "⎢t⋅sin(β + θ)  ────────────────────────── + ──────────────────────── - ───────\n",
       "⎢                        tan(α)                        2                      \n",
       "⎢                                                   tan (α)                   \n",
       "⎢                                                                             \n",
       "⎢                                                  ⎛   2       ⎞              \n",
       "⎢     t                                          d⋅⎝tan (α) + 1⎠              \n",
       "⎢     ─                                          ───────────────              \n",
       "⎣     R                                                 w                     \n",
       "\n",
       " 2       ⎞           ⎤\n",
       "n (α) - 1⎠⋅sin(β + θ)⎥\n",
       "─────────────────────⎥\n",
       "      2              ⎥\n",
       "   tan (α)           ⎥\n",
       "                     ⎥\n",
       " 2       ⎞           ⎥\n",
       "n (α) - 1⎠⋅cos(β + θ)⎥\n",
       "─────────────────────⎥\n",
       "      2              ⎥\n",
       "   tan (α)           ⎥\n",
       "                     ⎥\n",
       "                     ⎥\n",
       "                     ⎥\n",
       "                     ⎥\n",
       "                     ⎦"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "V = fxu.jacobian(Matrix([v, alpha]))\n",
    "V = V.subs(sympy.tan(alpha)/w, 1/R) \n",
    "V = V.subs(time*v/R, B)\n",
    "V = V.subs(time*v, 'd')\n",
    "V"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This should give you an appreciation of how quickly the EKF become mathematically intractable. \n",
    "\n",
    "This gives us the final form of our prediction equations:\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf{\\bar x} &= \\mathbf x + \n",
    "\\begin{bmatrix}- R\\sin(\\theta) + R\\sin(\\theta + \\beta) \\\\\n",
    "R\\cos(\\theta) - R\\cos(\\theta + \\beta) \\\\\n",
    "\\beta\\end{bmatrix}\\\\\n",
    "\\mathbf{\\bar P} &=\\mathbf{FPF}^{\\mathsf T} + \\mathbf{VMV}^{\\mathsf T}\n",
    "\\end{aligned}$$\n",
    "\n",
    "This form of linearization is not the only way to predict $\\mathbf x$. For example, we could use a numerical integration technique such as *Runge Kutta* to compute the movement\n",
    "of the robot. This will be required if the time step is relatively large. Things are not as cut and dried with the EKF as for the Kalman filter. For a real problem you have to carefully model your system with differential equations and then determine the most appropriate way to solve that system. The correct approach depends on the accuracy you require, how nonlinear the equations are, your processor budget, and numerical stability concerns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design the Measurement Model\n",
    "\n",
    "The robot's sensor provides a noisy bearing and range measurement to multiple known locations in the landscape. The measurement model must convert the state $\\begin{bmatrix}x & y&\\theta\\end{bmatrix}^\\mathsf T$ into a range and bearing to the landmark. If $\\mathbf p$ \n",
    "is the position of a landmark, the range $r$ is\n",
    "\n",
    "$$r = \\sqrt{(p_x - x)^2 + (p_y - y)^2}$$\n",
    "\n",
    "The sensor provides bearing relative to the orientation of the robot, so we must subtract the robot's orientation from the bearing to get the sensor reading, like so:\n",
    "\n",
    "$$\\phi = \\arctan(\\frac{p_y - y}{p_x - x}) - \\theta$$\n",
    "\n",
    "\n",
    "Thus our measurement model $h$ is\n",
    "\n",
    "\n",
    "$$\\begin{aligned}\n",
    "\\mathbf z& = h(\\bar{\\mathbf x}, \\mathbf p) &+ \\mathcal{N}(0, R)\\\\\n",
    "&= \\begin{bmatrix}\n",
    "\\sqrt{(p_x - x)^2 + (p_y - y)^2} \\\\\n",
    "\\arctan(\\frac{p_y - y}{p_x - x}) - \\theta \n",
    "\\end{bmatrix} &+ \\mathcal{N}(0, R)\n",
    "\\end{aligned}$$\n",
    "\n",
    "This is clearly nonlinear, so we need linearize $h$  at $\\mathbf x$ by taking its Jacobian. We compute that with SymPy below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$\\left[\\begin{matrix}\\frac{- p_{x} + x}{\\sqrt{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}}} & \\frac{- p_{y} + y}{\\sqrt{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}}} & 0\\\\- \\frac{- p_{y} + y}{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}} & - \\frac{p_{x} - x}{\\left(p_{x} - x\\right)^{2} + \\left(p_{y} - y\\right)^{2}} & -1\\end{matrix}\\right]$$"
      ],
      "text/plain": [
       "⎡          -pₓ + x                      -p_y + y             ⎤\n",
       "⎢───────────────────────────  ───────────────────────────  0 ⎥\n",
       "⎢   ________________________     ________________________    ⎥\n",
       "⎢  ╱         2            2     ╱         2            2     ⎥\n",
       "⎢╲╱  (pₓ - x)  + (p_y - y)    ╲╱  (pₓ - x)  + (p_y - y)      ⎥\n",
       "⎢                                                            ⎥\n",
       "⎢       -(-p_y + y)                   -(pₓ - x)              ⎥\n",
       "⎢  ──────────────────────       ──────────────────────     -1⎥\n",
       "⎢          2            2               2            2       ⎥\n",
       "⎣  (pₓ - x)  + (p_y - y)        (pₓ - x)  + (p_y - y)        ⎦"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "px, py = symbols('p_x, p_y')\n",
    "z = Matrix([[sympy.sqrt((px-x)**2 + (py-y)**2)],\n",
    "            [sympy.atan2(py-y, px-x) - theta]])\n",
    "z.jacobian(Matrix([x, y, theta]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Now we need to write that as a Python function. For example we might write:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import sqrt\n",
    "\n",
    "def H_of(x, landmark_pos):\n",
    "    \"\"\" compute Jacobian of H matrix where h(x) computes \n",
    "    the range and bearing to a landmark for state x \"\"\"\n",
    "\n",
    "    px = landmark_pos[0]\n",
    "    py = landmark_pos[1]\n",
    "    hyp = (px - x[0, 0])**2 + (py - x[1, 0])**2\n",
    "    dist = sqrt(hyp)\n",
    "\n",
    "    H = array(\n",
    "        [[-(px - x[0, 0]) / dist, -(py - x[1, 0]) / dist, 0],\n",
    "         [ (py - x[1, 0]) / hyp,  -(px - x[0, 0]) / hyp, -1]])\n",
    "    return H"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "We also need to define a function that converts the system state into a measurement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import atan2\n",
    "\n",
    "def Hx(x, landmark_pos):\n",
    "    \"\"\" takes a state variable and returns the measurement\n",
    "    that would correspond to that state.\n",
    "    \"\"\"\n",
    "    px = landmark_pos[0]\n",
    "    py = landmark_pos[1]\n",
    "    dist = sqrt((px - x[0, 0])**2 + (py - x[1, 0])**2)\n",
    "\n",
    "    Hx = array([[dist],\n",
    "                [atan2(py - x[1, 0], px - x[0, 0]) - x[2, 0]]])\n",
    "    return Hx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Design Measurement Noise\n",
    "\n",
    "It is reasonable to assume that the noise of the range and bearing measurements are independent, hence\n",
    "\n",
    "$$\\mathbf R=\\begin{bmatrix}\\sigma_{range}^2 & 0 \\\\ 0 & \\sigma_{bearing}^2\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Implementation\n",
    "\n",
    "We will use `FilterPy`'s `ExtendedKalmanFilter` class to implement the filter. Its `predict()` method uses the standard linear equations for the process model. Ours is nonlinear, so we will have to override `predict()` with our own implementation.  I'll want to also use this class to simulate the robot, so I'll add a method `move()` that computes the position of the robot which both `predict()` and my simulation can call.\n",
    "\n",
    "The matrices for the prediction step are quite large. While writing this code I made several errors before I finally got it working. I only found my errors by using SymPy's `evalf` function. `evalf` evaluates a SymPy `Matrix` with specific values for the variables. I decided to demonstrate this technique to you, and used `evalf` in the Kalman filter code. You'll need to understand a couple of points.\n",
    "\n",
    "First, `evalf` uses a dictionary to specify the values. For example, if your matrix contains an `x` and `y`, you can write\n",
    "\n",
    "```python\n",
    "    M.evalf(subs={x:3, y:17})\n",
    "```\n",
    "    \n",
    "to evaluate the matrix for `x=3` and `y=17`. \n",
    "\n",
    "Second, `evalf` returns a `sympy.Matrix` object. Use `numpy.array(M).astype(float)` to convert it to a NumPy array. `numpy.array(M)` creates an array of  type `object`, which is not what you want.\n",
    "\n",
    "Here is the code for the EKF:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from filterpy.kalman import ExtendedKalmanFilter as EKF\n",
    "from numpy import dot, array, sqrt\n",
    "class RobotEKF(EKF):\n",
    "    def __init__(self, dt, wheelbase, std_vel, std_steer):\n",
    "        EKF.__init__(self, 3, 2, 2)\n",
    "        self.dt = dt\n",
    "        self.wheelbase = wheelbase\n",
    "        self.std_vel = std_vel\n",
    "        self.std_steer = std_steer\n",
    "\n",
    "        a, x, y, v, w, theta, time = symbols(\n",
    "            'a, x, y, v, w, theta, t')\n",
    "        d = v*time\n",
    "        beta = (d/w)*sympy.tan(a)\n",
    "        r = w/sympy.tan(a)\n",
    "    \n",
    "        self.fxu = Matrix(\n",
    "            [[x-r*sympy.sin(theta)+r*sympy.sin(theta+beta)],\n",
    "             [y+r*sympy.cos(theta)-r*sympy.cos(theta+beta)],\n",
    "             [theta+beta]])\n",
    "\n",
    "        self.F_j = self.fxu.jacobian(Matrix([x, y, theta]))\n",
    "        self.V_j = self.fxu.jacobian(Matrix([v, a]))\n",
    "\n",
    "        # save dictionary and it's variables for later use\n",
    "        self.subs = {x: 0, y: 0, v:0, a:0, \n",
    "                     time:dt, w:wheelbase, theta:0}\n",
    "        self.x_x, self.x_y, = x, y \n",
    "        self.v, self.a, self.theta = v, a, theta\n",
    "\n",
    "    def predict(self, u=0):\n",
    "        self.x = self.move(self.x, u, self.dt)\n",
    "\n",
    "        self.subs[self.theta] = self.x[2, 0]\n",
    "        self.subs[self.v] = u[0]\n",
    "        self.subs[self.a] = u[1]\n",
    "\n",
    "        F = array(self.F_j.evalf(subs=self.subs)).astype(float)\n",
    "        V = array(self.V_j.evalf(subs=self.subs)).astype(float)\n",
    "\n",
    "        # covariance of motion noise in control space\n",
    "        M = array([[self.std_vel*u[0]**2, 0], \n",
    "                   [0, self.std_steer**2]])\n",
    "\n",
    "        self.P = dot(F, self.P).dot(F.T) + dot(V, M).dot(V.T)\n",
    "\n",
    "    def move(self, x, u, dt):\n",
    "        hdg = x[2, 0]\n",
    "        vel = u[0]\n",
    "        steering_angle = u[1]\n",
    "        dist = vel * dt\n",
    "\n",
    "        if abs(steering_angle) > 0.001: # is robot turning?\n",
    "            beta = (dist / self.wheelbase) * tan(steering_angle)\n",
    "            r = self.wheelbase / tan(steering_angle) # radius\n",
    "\n",
    "            dx = np.array([[-r*sin(hdg) + r*sin(hdg + beta)], \n",
    "                           [r*cos(hdg) - r*cos(hdg + beta)], \n",
    "                           [beta]])\n",
    "        else: # moving in straight line\n",
    "            dx = np.array([[dist*cos(hdg)], \n",
    "                           [dist*sin(hdg)], \n",
    "                           [0]])\n",
    "        return x + dx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have another issue to handle. The residual is notionally computed as $y = z - h(x)$ but this will not work because our measurement contains an angle in it. Suppose z has a bearing of $1^\\circ$ and $h(x)$ has a bearing of $359^\\circ$. Naively subtracting them would yield a angular difference of $-358^\\circ$, whereas the correct value is $2^\\circ$. We have to write code to correctly compute the bearing residual."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def residual(a, b):\n",
    "    \"\"\" compute residual (a-b) between measurements containing \n",
    "    [range, bearing]. Bearing is normalized to [-pi, pi)\"\"\"\n",
    "    y = a - b\n",
    "    y[1] = y[1] % (2 * np.pi)    # force in range [0, 2 pi)\n",
    "    if y[1] > np.pi:             # move to [-pi, pi)\n",
    "        y[1] -= 2 * np.pi\n",
    "    return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The rest of the code runs the simulation and plots the results, and shouldn't need too much comment by now. I create a variable `landmarks` that contains the landmark coordinates. I update the simulated robot position 10 times a second, but run the EKF only once per second. This is for two reasons. First, we are not using Runge Kutta to integrate the differental equations of motion, so a narrow time step allows our simulation to be more accurate. Second, it is fairly normal in embedded systems to have limited processing speed. This forces you to run your Kalman filter only as frequently as absolutely needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from filterpy.stats import plot_covariance_ellipse\n",
    "from math import sqrt, tan, cos, sin, atan2\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "dt = 1.0\n",
    "\n",
    "def z_landmark(lmark, sim_pos, std_rng, std_brg):\n",
    "    x, y = sim_pos[0, 0], sim_pos[1, 0]\n",
    "    d = np.sqrt((lmark[0] - x)**2 + (lmark[1] - y)**2)  \n",
    "    a = atan2(lmark[1] - y, lmark[0] - x) - sim_pos[2, 0]\n",
    "    z = np.array([[d + randn()*std_rng],\n",
    "                  [a + randn()*std_brg]])\n",
    "    return z\n",
    "\n",
    "def ekf_update(ekf, z, landmark):\n",
    "    ekf.update(z, HJacobian=H_of, Hx=Hx, \n",
    "               residual=residual,\n",
    "               args=(landmark), hx_args=(landmark))\n",
    "    \n",
    "                \n",
    "def run_localization(landmarks, std_vel, std_steer, \n",
    "                     std_range, std_bearing,\n",
    "                     step=10, ellipse_step=20, ylim=None):\n",
    "    ekf = RobotEKF(dt, wheelbase=0.5, std_vel=std_vel, \n",
    "                   std_steer=std_steer)\n",
    "    ekf.x = array([[2, 6, .3]]).T # x, y, steer angle\n",
    "    ekf.P = np.diag([.1, .1, .1])\n",
    "    ekf.R = np.diag([std_range**2, std_bearing**2])\n",
    "\n",
    "    sim_pos = ekf.x.copy() # simulated position\n",
    "    # steering command (vel, steering angle radians)\n",
    "    u = array([1.1, .01]) \n",
    "\n",
    "    plt.figure()\n",
    "    plt.scatter(landmarks[:, 0], landmarks[:, 1],\n",
    "                marker='s', s=60)\n",
    "    \n",
    "    track = []\n",
    "    for i in range(200):\n",
    "        sim_pos = ekf.move(sim_pos, u, dt/10.) # simulate robot\n",
    "        track.append(sim_pos)\n",
    "\n",
    "        if i % step == 0:\n",
    "            ekf.predict(u=u)\n",
    "\n",
    "            if i % ellipse_step == 0:\n",
    "                plot_covariance_ellipse(\n",
    "                    (ekf.x[0,0], ekf.x[1,0]), ekf.P[0:2, 0:2], \n",
    "                     std=6, facecolor='k', alpha=0.3)\n",
    "\n",
    "            x, y = sim_pos[0, 0], sim_pos[1, 0]\n",
    "            for lmark in landmarks:\n",
    "                z = z_landmark(lmark, sim_pos,\n",
    "                               std_range, std_bearing)\n",
    "                ekf_update(ekf, z, lmark)\n",
    "\n",
    "            if i % ellipse_step == 0:\n",
    "                plot_covariance_ellipse(\n",
    "                    (ekf.x[0,0], ekf.x[1,0]), ekf.P[0:2, 0:2],\n",
    "                    std=6, facecolor='g', alpha=0.8)\n",
    "    track = np.array(track)\n",
    "    plt.plot(track[:, 0], track[:,1], color='k', lw=2)\n",
    "    plt.axis('equal')\n",
    "    plt.title(\"EKF Robot localization\")\n",
    "    if ylim is not None: plt.ylim(*ylim)\n",
    "    plt.show()\n",
    "    return ekf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.025 0.042 0.002]\n"
     ]
    }
   ],
   "source": [
    "landmarks = array([[5, 10], [10, 5], [15, 15]])\n",
    "\n",
    "ekf = run_localization(\n",
    "    landmarks, std_vel=0.1, std_steer=np.radians(1),\n",
    "    std_range=0.3, std_bearing=0.1)\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I have plotted the landmarks as solid squares. The path of the robot is drawn with a black line. The covariance ellipses for the predict step are light gray, and the covariances of the update are shown in green. To make them visible at this scale I have set the ellipse boundary at 6$\\sigma$.\n",
    "\n",
    "We can see that there is a lot of uncertainty added by our motion model, and that most of the error in in the direction of motion. We determine that from the shape of the blue ellipses. After a few steps we can see that the filter incorporates the landmark measurements and the errors improve.\n",
    "\n",
    "I used the same initial conditions and landmark locations in the UKF chapter. The UKF achieves much better accuracy in terms of the error ellipse. Both perform roughly as well as far as their estimate for $\\mathbf x$ is concerned. \n",
    "\n",
    "Now let's add another landmark."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.021 0.02  0.002]\n"
     ]
    }
   ],
   "source": [
    "landmarks = array([[5, 10], [10, 5], [15, 15], [20, 5]])\n",
    "\n",
    "ekf = run_localization(\n",
    "    landmarks, std_vel=0.1, std_steer=np.radians(1),\n",
    "    std_range=0.3, std_bearing=0.1)\n",
    "plt.show()\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The uncertainly in the estimates near the end of the track are smaller.  We can see the effect that multiple landmarks have on our uncertainty by only using the first two landmarks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAz0AAAGDCAYAAAABN35ZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xd8FHX++PHXbM+m94QSgnQIRURUUAERuxQ7qGc59TwP9U7vaz9B/d7J79SznL0c4NfzRNGzYTsFpKggKL0FSEglve1ms3V+f+SyZsmmbPqE9/PxyMO7mfm0ee8M+96Z+YyiqqqKEEIIIYQQQvRRup7ugBBCCCGEEEJ0JUl6hBBCCCGEEH2aJD1CCCGEEEKIPk2SHiGEEEIIIUSfJkmPEEIIIYQQok+TpEcIIYQQQgjRp0nSI4QQQgghhOjTJOkRQgghhBBC9GmS9AghhBBCCCH6NEl6hBBCsGzZMhRFYdmyZT3dlSays7NRFIXrr7++p7vSIkVRmD59esCyxYsXoygKa9eu7ZE+HWvt2rUoisLixYt7uitCCNGtJOkRQhx3FEVp9W/btm3+7RsSgua+dL/yyivo9Xri4+P54YcfgF++XLb0l52d3WpfG9pu/Gc2m0lPT+faa69l165dnbFLukVvTqz6Cq0kiEII0d0MPd0BIYToKYsWLWp2XUpKSpvqeOSRR1i8eDFpaWl8+eWXjBw5MmD9oEGDmv0CGhMT0+a+jh8/nrlz5wJQXV3Nxo0beeutt1i5ciWrV6/mtNNOa3NdovssXLiQq666irS0tJ7uCgCTJ09m7969JCQk9HRXhBCiW0nSI4Q4bnXkFh+fz8fvfvc7Xn75ZTIyMvjiiy/o379/k+3S09M75VaiCRMmNKnn1ltv5ZVXXuHBBx9k9erVHW5DdL6EhIRelWBYrdYmibkQQhwP5PY2IYQIkdPp5IorruDll1/mjDPOYP369UETnq520003AbB58+ag6wsKCrjttttIT0/HZDKRmJjIvHnz+PHHH1us99NPP2XKlCmEh4cTGxvLZZddRmZmZofamD59OjfccAMAN9xwQ8i3+TWnPWNcsWIFM2fOJC4uDovFQnp6OvPnz2fLli3+baqqqnjiiSc466yzGDBggL/u2bNn891337W5f8Ge6Zk+fXqLtz02fi6ooKCARx99lKlTp5KSkoLJZKJfv37Mnz+f3bt3N2lr8ODBACxfvjygzoZbClt6pufAgQNce+219OvXz9/Otddey4EDB1oc18qVK5k8eTJWq5W4uDiuvPJK8vLy2ryPhBCiO8iVHiGECEF1dTVz5sxh7dq1zJ07l3/9619YLJYe6YvP5wPAYGh6Kj98+DCnn346hYWFzJw5k/nz55Obm8t7773HqlWreO+995gzZ06Tch988AGff/458+bNY/r06Wzbto3333+fNWvW8N133zFixIh2tXH99dcTExPDRx99xJw5c5gwYYK/nlBu8+vIGFVV5YYbbmD58uUkJCRwySWXkJiYSG5uLmvWrGHEiBFMmjQJgL179/Lggw9y5plncuGFFxIbG8uRI0f46KOP+Oyzz/j444+54IIL2tXv66+/vsmEBwDr169n9erVWK1W/7J169axZMkSZsyYwaWXXkp4eDiZmZmsXLmSjz/+mI0bN/r35fTp06msrOTZZ58NuB0SCNjfwWzatIlZs2Zhs9mYM2cOo0aNYu/evfzzn//ko48+4j//+Q+nnHJKk3IvvvgiH3/8MbNnz2batGls2rSJd999l23btrFjxw7MZnO79pEQQnQ6VQghjjOACqiLFi0K+vf4448HbL906VIVUM877zx1/PjxKqDecsstqsfjabaNNWvWqIA6aNCgoG2sWbOmTX1taPu6665rsu6WW25RAfXCCy9ssm7WrFkqoC5ZsiRg+fr161WdTqfGxsaq1dXVTdoB1E8++SSgzDPPPKMC6llnndUpbSxdurRNY2+QlZUVdB+E2v4rr7yiAurkyZPVysrKgDIej0ctKCjw///Kykq1pKSkSV+ys7PV5ORkdcSIEU3WAeq0adMCli1atEgFWo339u3b1cjISDUhIUHNzMz0Ly8qKgoYQ4OtW7eqVqtVPffccwOWN7evGjR8LhctWuRf5vV61REjRqiA+s477wRs//bbb6uAOnz4cNXr9TYZV2RkpLpjx46AMvPnzw9alxBC9CRJeoQQx52GL/fN/UVHRwds3zghANSZM2e22kbDl8vm/hp/6WxJQ9vjx4/3J0x/+MMf1MmTJ6uAmpqaqu7duzegTG5urj/hcrvdTepcsGCBCqjLly9v0s6xiY2q1icEQ4YMUQE1Ozu7w210RtLTnvYzMjJUQP3pp59Cav9YCxcuVAH1yJEjAcvbm/Tk5+erAwYMUC0Wi7px48Y29+Oiiy5SzWaz6nK5/Mvak/SsX79eBdSpU6cGLTNlyhQVUL/99tsm43rooYeabL969WoVUO++++42j0UIIbqaPNMjhDhuqfU//DT5q6ysDLr9ySefTFxcHN988w2PP/54m9qYNm1a0DZCndxg+/btPPLIIzzyyCM8/fTTbN68mbS0NDZt2tTkwfSff/4ZgDPOOCPorW9nn302AD/99FPQ/h5Lr9dz+umnB9TdkTY6Q6jt2+12du3aRXJyMieeeGKb2ti4cSNXXHEFAwcOxGw2+5+Pef755wHIz8/v8DhsNhsXXXQR+fn5LFu2jClTpjTZZtWqVVx88cWkpqZiNBr9/fj0009xOp2UlpZ2qA8N+3LGjBlB17cUy4bbARsbOHAgABUVFR3qlxBCdCZ5pkcIIdpo9OjRvP7668yaNYsHHngAh8PBo48+2i1tX3fddSxbtgxVVSkqKuL111/n4YcfZs6cOWzcuJGwsDD/tlVVVUDz026npqYGbNdYcnJy0DINdTWU6UgbnSHU9hsS2bZOOPHvf/+byy67DIvFwqxZsxgyZAjh4eHodDrWrl3Lt99+i9Pp7NAYvF4vV111FT///DOPP/44V155ZZNtnnvuOe68805iY2OZNWsWaWlpWK1WFEXhww8/ZPv27R3uR0diGR0d3WRZQxLq9Xo71C8hhOhMkvQIIUQIxo0bx7fffsvMmTN57LHHcDgcPPHEE93WvqIopKSk8NBDD1FVVcWTTz7JQw89xFNPPeXfpuGL6NGjR4PWUVhYGLBdY0VFRUHLNNTVUKYjbXSGUNtvmCyhrVdn/vSnP2EymdiyZQujRo0KWPeb3/yGb7/9tl39buyOO+5g1apV3Hzzzdx3331N1ns8HhYtWkRKSgo//fSTP/lo8P3333e4D9DzsRRCiO4gt7cJIUSIRo4cybp16xg0aBBPPvkkCxcuRFXVbu/Hww8/TGJiIn//+9/JysryL2+4fWvDhg14PJ4m5dasWQPAxIkTm6wL9mXe6/WyYcOGgLrb04Zer/fX11Ghth8eHk5GRgZFRUVs27at1foPHjzI6NGjmyQ8Pp/Pvy864qmnnuLFF1/knHPO4cUXXwy6TWlpKZWVlUyZMqVJwmOz2YLebtaefdywLxtPq91Yw/JgnxchhNAKSXqEEKIdhgwZwrp16xg6dCgvvPACN910k38K6e4SGRnJvffei9vtDnhGaMCAAcyaNYvs7GyeeeaZgDKbNm3i7bffJjY2lnnz5jWpc/Xq1Xz66acBy55//nkOHTrEjBkzGDRoULvbiI+PByA3N7dD425v+3fccQcAv/3tb6murg4o4/V6/Vc0oP6lspmZmQFXhlRV5ZFHHmHPnj0d6vsHH3zAPffcw9ixY3nvvfeCPpMEkJSUhNVqZcuWLdhsNv9yt9vNnXfeGfRZntjYWBRFCWkfT506lREjRrBhwwZWrlwZsG7lypWsW7eO4cOH+5/rEkIILZLb24QQx62WJhOYO3duq+82SUtLY926dcycOZN//OMfOJ1Oli9f7v+1vTvcdtttPPXUU7z11lvce++9jB49GoCXX36ZqVOn8j//8z989dVXTJo0yf8OG51Ox9KlS4mMjGxS3+zZs5k3bx7z5s1j6NChbN++nc8++4y4uLgmVyRCbeO0007DarXyzDPPUFZW5n9+6Pbbb2/XrVOhtn/TTTexYcMG3nzzTYYOHcqcOXNITEwkPz+fNWvWcOONN/o/E3/4wx+49dZbmThxIpdeeilGo5GNGzeyZ88eLr74Yj755JOQ+9vgmmuuwefzcfLJJ/O3v/2tyfr09HSuv/56dDodd9xxB0uWLGHs2LHMmTMHl8vFmjVrKC8vZ8aMGf4rWg0iIiI45ZRTWLduHddccw3Dhg1Dr9cze/Zsxo0bF7Q/iqKwfPlyZs2axZVXXsmcOXMYOXIk+/fv58MPPyQyMpI333wTnU5+JxVCaFhPTBknhBA9iVamrOaYaZVbeleOqqpqcXGx//09l156qepyufxTAx87hXGoWmtbVVX1ueeeUwH1kksuCViel5en3nrrrWpaWppqNBrV+Ph4dc6cOermzZubbWfp0qXqp59+qp566qmq1WpVo6Oj1UsuuUTdv39/0LZDaUNVVfXzzz9XTz31VDU8PNy/r7OyslrcBy1Nwxxq+6qqqm+99ZZ65plnqlFRUarZbFbT09PVBQsWqFu3bm2yT8aPH69arVY1Pj5enTt3rrpjx45mp6EOFu9g27b22Wtch9vtVp966il11KhRqsViUZOTk9VrrrlGzc7OVq+77rqg+y8zM1O96KKL1Li4OFVRlIDPc7Apqxvs27dPveaaa9SUlBTVYDCoKSkp6tVXX63u27evybYtTcXd2rTZQgjRExRV7YEb0YUQQgghhBCim8i1aiGEEEIIIUSfJkmPEEIIIYQQok+TpEcIIYQQQgjRp0nSI4QQQgghhOjTesWU1T6fr8n7LRRFQVGUHuqREEIIIYQQojdSVbXJS8F1Ol2LU+v3mqTHbrf3dDeEEEIIIYQQGhQeHt5i0iO3twkhhBBCCCH6NEl6hBBCCCGEEH2aJD1CCCGEEEKIPq1XPNMTbMKC1u7LE0IIIYQQQhx/gs0H0NoEaL026WltBgYhhBBCCCGEgNaTHskqhBBCCCGEEH1ar7jSoxUHDhzA4/FgMBgYPnx4T3dHtJHETbskdtokcdMmiZs2Sdy0SeLW/STpCYHD4cDtdmM0Gnu6KyIEEjftkthpk8RNmyRu2iRx0yaJW/eT29tCoCiK/09oh8RNuyR22iRx0yaJmzZJ3LRJ4tb9FFVV1Z7uhM/no6amJmBZZGSkTGQghBBCCCGECNCe3EGyCiGEEEIIIUSfJkmPEEIIIYQQok+TpEcIIYQQQgjRp8nsbSEoKSnB6/Wi1+tJTEzs6e6INpK4aZfETpskbtokcdMmiZs2Sdy6nyQ9ISgoKPBPLygfUO2QuGmXxE6bJG7aJHHTJombNkncup8kPUIIIYQQHVDn9PD/3tnAuh05pCVGMSo9kRvPO5GEGGtPdy1kOTk5pKWl9XQ3hOh0MmV1CCorK/H5fOh0OmJiYnq6O6KNJG7aJbHTJombNknc2u+SP61g++Gj2F3V6BUDFkMYUeFh3HLRRG6+8CQMhq77PtOZcVu5ciVXX301zz//PDfffHMn9VAEI8dbx7Qnd5CkRwghhBCinQ4XVnDuH/+PotoC6rx2AHToiTbFEWmOYfSgRF7948WkxEX0cE9b9tJLL/G73/0OVVXR6XR8++23nH766T3dLSGCkvf0CCGEEEJ0o7XbslEBp9dBeL/DJE/YgCkhlwpXCYW2HHZmFTLvT++w/eDRnu5qUKqq8tBDD3HbbbfR8Dv4ddddx6mnntrDPROic0nSI4QQQgjRTrZaFyoqKj5M4TVYIm0kj9pBYsYmvIZqCmtzySst5+o/f8DnP2T2dHcDeDwebrrpJv785z/7l91333288cYbGAzy2LfoW+QTHQKPx4OqqiiKIicDDZG4aZfETpskbtokcWufxBgrOhQUdHjdJv9ya2wFxgnfUbxnIkV2Lx5fMne99BUen4+Lp4zotPbbGze73c6VV17JqlWrAFAUhWeffZbbb7+90/ommifHW/eTvRyC3bt3+6cXHD9+fE93R7SRxE27JHbaJHHTJolb+yREhwOgU/R4nZaAdUaLk5RxP1CyfwJl5fXL7nnla4wGPedNHtop7bcnbqWlpVx44YVs3rwZAJPJxFtvvcXll1/eKX0SrZPjrftJ0iOEEEII0U4Th6WAomDSmXFWxzdZrzeoJI38meL9Eygrq7+icveLXxEZZmLq2O6fGjorK4vzzjuPAwcOABAVFcVHH33E9OnTu70vQnQnSXpCEBUVhcfjkcuQGiNx0y6JnTZJ3LRJ4tY+8dFW0lNiqD5SicMehcdlwGDyBGyj00PSiG0U79VRWgEKOm575jOW3zeHCcNSO9R+KHHbtm0b559/PkeP1k+q0K9fPz7//HPGjRvXoT6I0Mnx1v1kymohhBBCiA6479WveWfNdgrs2cSN+InIpOKg2/m8CkW7JuGuTiQprB/JMbGsePgyhvSP6/I+fvPNN8ybN8//fWvkyJF88cUXDBo0qMvbFqKzyZTVQgghhBDdbNr4QRh1RgyKidrSlGa30+lVksZsRR9eQbGjgJKqam57ZhWOOneX9u+dd97h/PPP939JPO2009iwYYMkPOK4IkmPEEIIIUQHnH3SCURYzVgNEdRVpOB165vdVm/wkZzxIzqLjRJHIQcLyrnvta+7rG9PP/008+fPx+2uT6xmz57N119/TXx80+ePhOjLJOkRQgghhOgAo0HP9PGDiDBFgU+HraTl53QMJg8JI3/Co9RRWnuUz37I5M0vt3dqn3w+H3fddRd33XWXf9ktt9zC+++/j9Vq7dS2hNACeXoqBIcPH/Y/dHbCCSf0dHdEG0nctEtip00SN22SuHXMNbPG8en3BzDrrNiODiS6X16L21sibcSesJuKg2Opdlby//61gfFDkhk/tPnb44IJFjeHw8E111zDBx984N9u8eLFPPzwwyiKEvrgRKeT4637hXylp6amhnvuuYdzzjmHxMREFEVh8eLFQbd1u9387W9/Y+zYsYSFhRETE8OUKVP47rvvOtrvHlFTU0N1dXWTB6dE7yZx0y6JnTZJ3LRJ4tYxJ43ox5B+cUSYovDYo3FUR7ZaJio1n7CkPCpcpVTX2bn9uc+pstWF1O6xcSspKWHmzJn+hEev1/P666+zaNEiSXh6ETneul/ISU9ZWRmvvvoqTqeTuXPnNrud1+tl3rx5PProo8yfP5/PP/+cf/7zn5x33nnY7fYOdVoIIYQQore55MxRhBsj0Sl6bEcHtqlM/JDdGKzVlDoKySut4vfPf0F7J9Y9ePAgU6ZM4fvvvwcgIiKCVatW8etf/7pd9QnRl4Q8ZXXD5oqiUFpaSmJiIosWLWpyteeZZ57h7rvvZuPGjZx66qkt1qmVKau9Xq//f+v1zT+kKHoXiZt2Sey0SeKmTRK3jquxOzlt4RsUVh+lxltGv0lrMJpbn5nNVRvG0W1TMatRJIf35/ZLTuGOS09pU5sNcfv++++ZO3cuZWVlQP07eFatWsWECRPaPyDRZeR465humbJaUZQ2XR599tlnOfPMM1tNeLREr9f7/4R2SNy0S2KnTRI3bZK4dVxkuJkLThlGtDkWxWegMmdIm8qZrA5ih+2kzldLZV0ZL370Ixt35rSprF6v58MPP2TWrFn+hCcjI4MffvhBEp5eTI637tcll1Jyc3PJzs5m7NixPPDAAyQnJ2MwGBgzZgzLly/viiaFEEIIIXrcHy4/lTCTmQhjNLVFabjqzG0qF5lYRHi/LKrcFdicNu568StKKlp+HEBVVZ5++mkuv/xy6urqnwWaOXMmGzZsYODAtt1eJ8Txoktmb8vPzwdg+fLlDBgwgOeff57o6Ghee+01rr/+elwuFzfffHOLdezevZtBgwYRFRXlX+Z0Otm3bx8AsbGxpKWlBZTJzMyktrYWgPHjxwesKy0t9fcrLS2N2NhY/zqv18uuXbuA+ktjx86ikZWVRXV1NQBjxozBYPhlt1VWVnLkyBGg/lJyYmJiQNkdO3agqiphYWEMHz48YF1ubi7l5eUAjBgxAovF4l9ns9k4dOgQAElJSaSmBk5/uWfPHtxuN0ajkdGjRwesKywspLi4/m3QQ4YMISIiwr+urq6O/fv3AxAXF9fkpHjgwAEcDgeKojBu3LiAdSUlJRQUFAAwaNAgYmJi/Os8Hg+7d+8GICoqisGDBweUPXz4sP8yZEZGRsAvGxUVFeTk1P+i1b9/fxISEgLKbt9eP42n1Wpl2LBhAetycnKoqKgA6t8ubTb/8o9LdXU1WVlZACQnJ5OSEjgjzu7du/F4PJjNZkaOHBmwrqCggJKSEgCGDh1KeHi4f11tbS2ZmZkAxMfHM2DAgICy+/fvp66uDr1eT0ZGRsC64uJiCgsLAUhPTyc6Otq/zuVysXfvXgCio6NJT08PKHvo0CFsNhsAY8eODbiEW1ZWRl5e/UxBAwYMCHj/gs/nY+fOnUD9/d1DhgT+8pidnU1VVRUAo0aNwmQy+ddVVVWRnZ0NQGpqKklJSQFld+3ahdfrxWKxMGLEiIB1eXl5/l8dhw0bFjBFqt1u5+DBgwAkJibSr1+/gLL79u3D6XT6fyxp7OjRoxQVFQEwePBgOUcg5wg5R9STc0S93nCOmHfGSP71jQubu4qqnCHEDN6Oz+cDwGQyBdwx4/V68Xg8AEQP3IOrJobSGh2mKjP3v/4Nd5ybHvQc4fV6uemmm1i2bJl/2XXXXcerr76KyWSSc0Qjco6o15fOEQ3HaSi6JOlpOLDr6ur47LPP/G/8nTVrFpMmTeLRRx9tNenxeDxNHuRTVdX/cq2GE8SxZRrWB+tTw7qG/jXW1nrLy8sxGo3+k13jehvfn9m4XlVVMRqNTdZ5vV5/2WPH2pZ6mxtr43qPHWvjfRis3oaxBruFsa319lRsWvq82Gw2KioqAv6RcrvdeDyeoPd/thSb1vZhQ2yCrWup3sZjDTXmbd2Hwco37tOxWhury+XC5/MFvTzfWfuwrKwMnU7nj11b6+0tn8Pj9RxRXV2Nqqr+uPXG2LTlc3i8nSMcDkeTc2VvPkcE20e94Rzx+8tO4aON+4h0xlBdPBBr8gH0ZlvQehv3U9GrJI7cRuFPZ1DmKObbbXpGJemZNiY54BxRW1vLggUL+Oijj/zL7r77bp544gn/sdnbzxFa+x7RVeeIYF/ee/M5ojd9jwhVlyQ9DdnhyJEj/QkP1D8PdO655/L4449TXFzcJNsL6JjB0OSAURTFf9A3/iW1cZlgXxwAdDqdf12wD2db6nW73eTk5AQkPY3rDRYwo9GIqqpB69Xr9f6yx461LfU2/m9z9R471sb7MFi9DWMNdrJqa709EZuGPgTrk9vtprKyErvdHvAPecM4W9uHLX0Om4uN1+sNuq6lehuPtbl6O7oPWxvrsVobq8lkwuv1dsk+bDgBZ2VlBRxzba23t3wOj8dzhNvtpri4OODLc2+MTVs+h8fTOcLtdlNXV0dOTk7AubI3nyNCPW6663OYEB3OFdPHsOxLN7aaKmryRxA75Keg9Tbup6IoGCxOYgbvoeLgOGwuG0tXH2TysCSiour7W1RUxJw5c9i0aZN/vA888ACXXHJJwHh78zmitXqPh3NEg4YrL8fW2xvPEY3/21yfjtWV54hQhTx7W2PNzd7m8XiIjo5m6NCh/kuKDe6//36WLFlCSUmJ//KjVmZv2759u/9S8LGXvUXvJXHTLomdNknctEni1rkqbXVM//0yCiqLqHSXkDJhPeaItt2So6pwdOckPFXJ9ItI54LJw3n+9xewe/duLrzwQv8ts5GRkfz1r39l0qRJEjeNkeOtY9qTO3TJlR6DwcCcOXNYuXIl2dnZ/nsKVVXliy++YMiQIU3ut9SC/v374/P5el0yJlomcdMuiZ02Sdy0SeLWuWIiLCyYOZZXP3VS7a6kMmcoyaN3tKmsokD8sF0U/hRLuaOYL3/U8efnlvLXP/3e//xg//79+eyzz+jXr5/ETYPkeOt+7brS8/nnn2O326mpqeHGG2/k8ssv54orrgDgggsuwGq1cujQISZNmkRycjKLFy8mKiqK119/nQ8//JB3332Xyy67zF+fVq70CCGEEEK0la3WybTfLye3/CiVrhKSJ2zAEhn82R6P10d2YSUA6akxGPQ6KvMHUnV4DNb8HKp+/hTU+mctTjrpJD7++OMmEzwIcbxoT+7QrqQnPT3df2n1WFlZWf4rO7t27eK+++5j3bp1uN1uJkyYwIMPPshFF13U4Y4LIYQQQvR2z72/iec+2ES+LQt9TD6pGT8H3S5Y0uPzquQsM+LZv8+/3dy5c3nrrbcCZgMT4njTbUlPZ5OkRwghhBB9UZ3Tw5m/X0pO6VHKncUkjNlMeFy5f73HW3/1xuvzkVtUf+vawOQoFDeUvFOMY98vzwHFjTmbtR/9H2OHBE6dLMTxpj25g2QVQgghhBBdxGI2cOvsSUSaojHqLFQcGoPP+8vMU9mFlWQXVvoTHoDcg5XkPJ/7S8KjU9CPO4uIjHNZtOzboFMKCyFa1iUTGfRVMtOGNknctEtip00SN22SuHWd68+dwAfr9uLMcnK01kll7mDi0g8H37jYA5/UgL3+RhydRUfSgn5UVA+mrK6YnYdNvP31Lq45p/7FnxI3bZK4dT+50iOEEEII0YV0OoXHbpyBxWghwhBFTf5QXLVhQP3zO+mpMQxMjoJDLlhZ7U94DHEGBiwcQMRIC7En7MHlc1DjquaZ93+gptbZk0MSQnMk6QmB1WolPDwcq9Xa010RIZC4aZfETpskbtokcetaJw5L5dIzRhFrSUSnmig7NBpVBYNeh16nYNtQDats4Knf3pJuYeDtAzElmQCISCjBHFtMpauMCpuDlz7aAkjctEri1v1kIgMhhBBCiG5QY3dy9h/fJKesmLK6o8QO/5nI+KMUf1BMzZZfvgeFT4gg5YpkFEPgW+edtnCO/nwG0cYE+scms/bp64mJtHT3MITocTKRgRBCCCFELxUZbuaeq6YSYYzEogunYu8J5L1cEJDwxJ0TR8r8pgkPgDnCTlhCATXuCmp/RP1sAAAgAElEQVRq63j+35u6s/tCaJokPUIIIYQQ3eTSaaOZkjGQSKcH95oPceY4AFAMCskLkok7Ow5FaZrwNIgZlIlP8VLlrODdtXsoqbB3V9eF0DSZvU0IIYQQmuP2eHn10628s3o3FpOBtKQorpg+hnNOHtJi0tAbTBtQx1tfPw+e+skIdBFG+t2QjGVg67eqmawOwhLzqCnWY6uL5dkPNvG/vz6rq7sshOZJ0hOCnJwcPB4PBoOBtLS0nu6OaCOJm3ZJ7LRJ4qZNWovbY/+3jnfX7KKyrhIVlX15ZtbvyGHM4CQevWE6Y09I7ukuNqGqKo8//jgPPvigf5kuJgXDaWdhTNkKeNtUT2zaQQpK+lPlLOfd1Tu5cEIS/ROjNBE3UU9rx1tfILe3haCiooLy8nIqKip6uisiBBI37ZLYaZPETZu0FDebw8Wn3x2gzFFKeV0JFa6jFNXmUWjPZevBHK58ZCVvf72zp7sZwOFwcM011wQkPGljT6f/2XeCIYHSg2No69RSxrA6wpNzsLmrqHXW8dInP2sibuIXWjre+gpJeoQQQgihKZv35mOvc2N312BJyiZl8pfEjPwRj6mYo/ZcymrLWLRsLfe/9g1er6+nu0tBQQHTpk3j7bff9i/7y1/+wrr/fEJ0ZDSx5gTqSvtRXTigzXXGDDyEqvNQ465i/Z4iCsrk2R4hWiK3t4Vg5MiRqKra6+8VFoEkbtolsdMmiZs2aSluDqcbn8+HV/VisdZgNuowJ5YREbuRssMjqShScfmcvLdWpaTSzkt/uBCjQd8jfd2yZQtz5syhoKAAgPDwcN566y3mzp0LwANXn87D/1hDnddB5eHRmCKqCIuqaalKAAwWF+EpR7AXnICqS2DVjnLOl0d7NENLx1tfIVd6QmA2m7FYLJjN5p7uigiBxE27JHbaJHHTJi3FLeB7ovrL/9EbIHHYXqKHbMfuqaS4Np+127K49elVPXLFZ8WKFZxxxhn+hCctLY2NGzf6Ex6A+TPHMnvqCOLDkjFgoXTfRLyutv0mHTPwMOg8VLnK+c9P2WQVyq1SWqGl462vkKRHCCGEEJoSaa3/oqhDj88VOOOZoijE9CskbuQW6lQbxbUFfLstmz+88CU+X/e8j93n8/HQQw9x1VVXUVdXB8DUqVP58ccfGT9+fJPt/3LTTIYPSCDJ2g/VGU7JgXFt6qvB5CYiNZtaTzVuj4flX2zv9LEI0VdI0iOEEEIITRkxMAGdTsGoM+GujUINMgNAZEI58SO3UOezU+Io5LNNmTz0j9VBt+1MVVVVzJ49mz//+c/+ZTfccAPffPMNSUlJQcuYTQZe+sOFxIaHE29JxlmRRGXuCW1qL6pfDqqiUuOsYtWmTDyenn+GSYjeSJKeEFRXV1NVVUV1dXVPd0WEQOKmXRI7bZK4aZOW4pYYYyUq3IJJb8ZTG4Wvme/5EfHlxA77GYe3hjJHEe+t2c3fP9jcZf3at28fkydPZtWqVQDodDqeeuop3njjjVZvY0pPieHPN80k3BRJhCGGmtwR1FbEttqm3uTAFF2EzV1FZY2DT77f3yljEV1LS8dbXyFJTwiysrLIzMwkKyurp7siQiBx0y6JnTZJ3LRJS3FTFIWRafFYDGGobjPO2vBmt41KLib6hJ3YPdVUOMt4/sPNbNyZ0+l9+uSTT5g8eTIHDhwAIC4uji+//JK77rqrzQ+rX3DqMH51zjjiwhIxKRbK9p+I22lqsYzb7caSkIVHdeHwOFixZneHxyK6npaOt75Ckh4hhBBCaM7pGWlY9GEoig5HefDbxhrE9CsgvP8hql0V1Lpqufulryirqu2Ufvh8Ph577DFmz55NTU39rGtjx47lxx9/5Oyzzw65vgeuPoPxQ1NItKaCO4ySfROavZLVwBJThM5Uh81VxU8HCskrkasHQhxLv3jx4sU93QlVVXG5XAHLzGZzr5zGLzw8nMjISCIiInq6KyIEEjftkthpk8RNm7QUt4QoK//3n53UeRy43BCZktvi9wZLdDmOyjjstSo6Xxg7D5dwyZmjOvRdo6amhquvvpoXX3zRv+zyyy/nk08+ITk5uV116nQK08cP4qONB/B49NTYvXhcRqxxpTTXVb1eh8dlwlEdRaQxhqhwM6eObvs7f0TP0NLx1tu0J3eQpCcEERERREVFyYdTYyRu2iWx0yaJmzZpLW4xkRY++yGT8hoHdocHS2I+BqOn2e0VBSwxpdQUpeJ0uamqVlB9cOqY9iUHhw4d4uyzz2bdunX/rV/hL3/5C88++ywmU8u3pLUmIszEqLQEvtiUDapCTbURrw+sseVNttXpdOh0OgwmF7ajaRgVE06nwvyZYzvUB9G1tHa89TbtyR3k9jYhhBBCaNL5k4diNUagoGAvSW11e6PFSdywHTh9Dirrynjp4y18tys35Ha//PJLJk2axO7d9c/PREdH8+mnn3L//fd32g+2p48bxP1Xn060OYYoYxy2vKFU5A5qdntzhB292YHDU0tmfhk1dmen9EOIvkKSHiGEEEJo0iVnjEKn6LDow3GU9G/Tu20iEkrrn+9xV2B32bnrxS8pr3a0qT1VVXniiSe44IILqKysBGDkyJFs3ryZCy64oENjCeb68yaw8JJTiLXEE2GIoTp7FFUF/Zvd3hRdhtPnwOPxsWFX50/WIISWSdIjhBBCCE0amBzN6EEJRJqi8ToisJcntKlcXHomxsgySuuOUlxZwx3Pfd7q+3vsdjsLFizgnnvuwfffmQVmz57Npk2bGD58eIfH0pw7Lz2F686dQHxYIlZ9FJWHxlJVGDzxscSU4VXduH0eNnTBDHVCaJk80xOC3bt3U1BQQFlZWbMvGBO9j8RNuyR22iRx0yatxi3MbGTNTznUeuy4nEYikvNa/f7wy/M9/XC6PFRWgUGnY/Ko4MlEZmYms2bNYvXq1f5lixYt4qWXXsJisXTqeII5Y1wa+aU1HClw4Pa6qSmLQcWLJboSl9uJ1+PF6/NiNIKtMB2zLozE6CjmnTGqy/sm2kerx1tvIc/0dDGPx+P/E9ohcdMuiZ02Sdy0Satxmz1lBP0To4gyxeKujsNRFdOmcvXP92zH6aul2lnBSx9v4UhRZZPtPv74YyZNmsSuXbsAiIyM5IMPPmDx4sXodN3zNUpRFJbccjaXnjmKRGtK/a1uOSMo2TcWn1dXf5VKBYO5/kugV/VSUVPXLX0T7aPV403LJOkJgdls9v8J7ZC4aZfETpskbtqk1bjpdAo3nj+BcGMkBsVIVd4JbS4bkVBKWFIuVa5y7HV1PPT6L1dyvF4vDz30EHPmzKG6uv69N6NGjWLz5s3Mmzev08fRmobE54bz6291izMn4SgdQNme03HbY1AUBUXnAwV8qpdqmcigV9Pq8aZlitraTazdwOfz+V/o1SAyMrLbfkERQgghhHa5PV7OuGMpWSWFVDiLST5xPZYIe5vKel0G8n86E7M3luTwfjxx6yzOGJ3E1VdfzZdffunf7vLLL+eNN94gMjKyq4bRZu+u2cUjy7+l2mGjtK4Ir+omLKEAnd6LvWggiZZ+TBs3nLcfurSnuypEl2hP7iBZhRBCCCE0zWjQc82scUSaotEpBqpyB7e5rN7kISZ9L3U+O3a3jT899zYnnXSSP+HR6/U8+eSTrFixolckPABXzMhg2X1zSU9Oon9EOtHGeFxlg7AXDcSgmLEYrJzazPNJQhyv5EqPEEIIITTP7nBx+u3/IK/yKFXuUlImfovZ2vS5Fp9P5XBBBQAn9ItFp1NQVTi6cxLOXWV4d6xB9dU/Z5GYmMiKFSuYMWNGt46lreqcbl748EeWfbmdOqcbr+pDp+gYNiCepffMJiW+dyRpQnS29uQOkvQIIYQQok/4yz/X88ZnW8mrySIs5TCJw/Y12aZx0gP1iY/ig6L3K7BtLfcvH3/iSXz68YcMGDCgW/reEaVVtfywJ4892SUkxli5ckYGVouxp7slRJdpT+5g6OpO9SUFBQV4vV70ej39+vXr6e6INpK4aZfETpskbtrUF+J260Un8fbXO4k0RlNdnIZ7YBZGS/0D/Q0vLvUd81uvq9JNyT+LcOb+8uB/xNDTGDXnTk0kPA1xmzgogotO67r3BYnO1ReON62RSykhKCkpoaioiJKSkp7uigiBxE27JHbaJHHTpr4Qt7hoK7OnjCDKHIfOZ6Q865ck4HBBBYcLKsgubDQtda6bvGdz/QmPYlAwnDQdZcyZbDlQxBebD3b3EELWF+J2PJK4db+Qk56amhruuecezjnnHBITE1EUhdbeb6qqKmeeeSaKorBw4cL29lUIIYQQokV3X3EaUVYLUaY46kr746iKbrqRqsJmB/y7Bhz/vfITpWPA7wYQd6ZKnc9OrbuW//evjXg8vu4dgBCiS4R8e1tZWRmvvvoq48ePZ+7cubz++uutlnnhhRc4eLD3/1rSmqFDh6Kqaqtveha9i8RNuyR22iRx06a+Erf4aCu/ufgknnr3e2zuKsoPjSZ1wnec0C+2/lkehw++tEOO+5dCg4xwbjjm/mZMaj41hWlU1JrILbbyzppdXDNrXM8NqBV9JW7HG4lb9ws56Rk0aBAVFRUoikJpaWmrSU92djb3338/b775Jpdcckm7O9obhIeH93QXRDtI3LRLYqdNEjdt6ktxu/nCiby3dg91nkSK7S5qivoTnVpAP3cYRe8exVvlrd9QgZhZscROj0XR1X/5VBSIHXSAkj3R2F02ln2xjflnZaDX984nAvpS3I4nErfuF/IRrChKSFnpLbfcwqxZs3rk7cVCCCGEOP4YDHruX3A6YQYrFn04ldkjKF9bTcEr+b8kPGEKzI0k7qw49AYdOt0v323C4sowhFdT7aog+2glq37I7KGRCCE6S5fO3vb666+zefNm9uzZE3LZ3bt3M2jQIKKiovzLnE4n+/bVTz8ZGxtLWlpaQJnMzExqa2sBGD9+fMC60tJS8vPzAUhLSyM2Nta/zuv1smvXLqB+ursTTjghoGxWVhbV1dUAjBkzBoPhl91WWVnJkSNHAOjXrx+JiYkBZXfs2IGqqoSFhTF8eOCsKrm5uZSX10+POWLECCwWi3+dzWbj0KFDACQlJZGamhpQds+ePbjdboxGI6NHjw5YV1hYSHFxMQBDhgwhIiLCv66uro79+/cDEBcXx8CBAwPKHjhwAIfDgaIojBsXeDm/pKSEgoICoP6KX0xMjH+dx+Nh9+7dAERFRTF4cOCL4Q4fPuyfWjAjIwO9Xu9fV1FRQU5ODgD9+/cnISEhoOz27dsBsFqtDBs2LGBdTk4OFRX1U4+OHDkSs9nsX1ddXU1WVhYAycnJpKSkBJTdvXs3Ho8Hs9nMyJEjA9YVFBT4Hy4cOnRowC8ytbW1ZGbW/wMYHx/fZHaf/fv3U1dXh16vJyMjI2BdcXExhYWFAKSnpxMd/cu95i6Xi7179wIQHR1Nenp6QNlDhw5hs9kAGDt2bMC0jGVlZeTl5QEwYMAA4uPj/et8Ph87d+4EICIigiFDhgTUm52dTVVVFQCjRo3CZDL511VVVZGdnQ1AamoqSUlJAWV37dqF1+vFYrEwYsSIgHV5eXmUlZUBMGzYMKxWq3+d3W733/KamJjYZOaaffv24XQ6MRgMjBkzJmDd0aNHKSoqAmDw4MFyjkDOEXKOqCfniHoN54gkE0wansLGnTbyvltJeWGxfxvTIBOumVaICPzt1+Vy0fAmj+gBhynbH0Wdu5Y3PvuJ04bH+T/fco6QcwTIOaJBT5wjGv4tD0WXJT35+fn88Y9/5K9//Wu7puLzeDwc+wohVVVxu93+9cHKNKw/ls/n86/z+Zo+lNjWeu12O0aj0b/jG9fr9XqD1quqKkZj0/nyvV6vv+yxY21Lvc2NtXG9x4618T4MVm/DWINdzWtrvT0Vm5Y+L3V1ddTW1gYcMG63G4/HE3RO95Zi09o+bIhNsHUt1dt4rKHGvK37MFj5xn06Vmtjdblc+Hy+gH98gtXb3n3o8/mw2+0oiuKPXVvr7S2fw+P1HOFwODCZTP649cbYtOVzeLydI5xOZ5NzZW8+RwTbR43rvezEaD546hnUml9myIo8PZKomVEYTIagx11DneGJR6k8UkuVq4I92VY27spjQGR9X3rjOaK2tjYg6ent5witfY/oqnOE0+lsUrY3nyN60/eIUHVZ0nPrrbcyfvx4br755naVNxgMTQ4YRVH8B33jX0kalwl2UgDQ6XT+dcE+nG2p1+12k5mZidFo9P9K3LjeYAEzGo2oqhq0Xr1e7y977FjbUm/j/zZX77FjbbwPg9XbMNZgJ6u21tsTsWnoQ7A+ud1uSktLqaqqCvh1v2Gcre3Dlj6HzcWmYe79UOptPNbm6u3oPmxtrMdqbawmkwmv19sl+7DhBLx3796AY66t9faWz+HxeI5wu93k5+dTXFzsj1tvjE1bPofH0znC7Xb7f4FufK7szeeIlo6bDz/8kCVLluCqq/tvITPGyVOImnUIna75L0wNfVEUiOp/mIpDVpweJ29+s5dFl9dfVepN54gGOTk5xMXFhVRv4/8eW698j+jac0SDhiskx9bbG88Rjf/bXJ+O1ZXniFApantSpf8qLS0lMTGRRYsWBUxbvXLlSubPn8+GDRsCLlXFxsZy880389e//pXw8HD/QNrzVtWesH37dv+l4GNvjRG9l8RNuyR22iRx06a2xm1PdjE2h5vU+AgGJEb1utmnamtrWbhwIUuXLvUvi0xOJ3zSlZTp7EQOPEBc+uE21aX6dOT9OA2zJ56kiH6sePgyJg5Pbb1gN5LjTZskbh3TntyhS6707Nq1C4/Hw6mnntpk3WuvvcZrr73Gv//9b+bOndsVzXeZ+Pj4ZjNv0XtJ3LRLYqdNEjdtai1upVV2/uel/7BhV279e26Aof3juOXik5gzdUSv+KFy7969XHnllf7nD6D+zpMFv7mbXz/1OU57MTV5wwmLKScsprKFmuopOh+RqVlUHbHg8rh46eMfee2Ps7tyCCGT402bJG7dr0uSnuuvv57p06c3WT5jxgzmzp3LnXfe2eTBLC049kEzoQ0SN+2S2GmTxE2bWovbY2+u49sdWZTVFuNWXRgUI7XZtdzzcjn/958dvHDHBaQmRHZTb5tavnw5t912m/8BZ6vVymuvvcaCBQsAmH9WBv/8eidOm4PS/RNIPXEDBlPTZzyOFZmaS3XeUKqc5azbfoTMvDKGDYhvtVx3keNNmyRu3a9dSc/nn3+O3W73X1bas2cPK1euBOCCCy4gPT29yYwRDfr37x80IRJCCCFE73SkqIqvthymsq4ch8+GJaEQjz2SEocdkysMT6aHix/8F3/9zSzOmji49Qo7kc1m43e/+x1vvvmmf9mYMWN49913A2Yl+9O10/g58yieLDeFdjel+8eTnLGV1u7O0xu9RKQewZZnxO1J4K3/7OCRG2Z01XCEEF2kXUnPb3/7W//0igDvvfce7733HlA/LWNzCY8QQgghtGfr/gLcHi+1HhvW5BwSh+9BVcFemkjFoQwK7S5c3mRue2YVj904g8unj2m90k6wY8cOrrzySv9U9QA33XQTzz77bMAMdAAGg46/33E+8x5egdOTTFmlj8rcdGLTslttJzIll5q8IdhcNXy77Qgerw9DL31ZqRAiuHYlPQ3zbYeqA3MmCCGEEKKHFFfaQVXx4cUUXn+Xh6JARGIJlqgNlOwfT0mVD6/q4cE3VqOqcMWMrkt8VFXltdde484776Tuv7OzRURE8Morr/hvZwtmUEoMj1w/nbte/Aqnt5bqnJFYoipbfb7HGFaHMaKKWnsY+aXVbN1fwCmj5fYkIbSkS19O2tfs37/fP9PGsS9QEr2XxE27JHbaJHHTppbiZnO48KECKjpD4HMwBrOb5IwtlB7IoLxERQX+9I81WEwGZk/t/PhXV1dzyy23sGLFCv+yCRMm8O677zZ58WQwF08Zwaa9+byzWsVpq2vz8z3hiYVU2mJwez18tHF/r0l65HjTJolb95NrsyGoq6vz/wntkLhpl8ROmyRu2tRS3BKjregUHQoKHqe5yXqdDhKG7yQsKZcKZwnVdVXc++rXfL21bVNDt9XWrVuZOHFiQMKzcOFCvv/++zYlPA0WXzed0YMSSbSmorqslO4fT2s3o1gTCgGVWncN3+/Jxe1p+qLFniDHmzZJ3LqfJD0h0Ov16HQ6mV5QYyRu2iWx0yaJmza1FLf+iVEogE4x4HVZgpbX6RQShu3CkpBPmbOIKkc1//Pyf8gtbvryxVCpqsrf//53pkyZwqFDhwCIjo7m/fff5+9//zsWS/A+Ncdg0PHcHecTGxFBnDkJZ2UiFUeGtljGaHFijKjG4aklr7ia/bll7R5PZ5LjTZskbt2vQy8n7SxaeTmpEEIIcTw6lF/Oefe8xVF7PmpkLqnjfmx2W58XivZMxF2ZQmp4GhOG9Gfl4ssxGNr35a6iooIbb7yRDz/80L9s8uTJvPPOOwwe3LGZ4j7euJ+7X/qK8toSajwVxAzeS/SAI81uX5E1jJq84QyISOf+BWdw00Undah9IUT7tCd3kKxCCCGEEC0anBpLTIQFk96MuyYG1df8PM86PSSN2IFiqqXEcZRdWcUs+dfGdrW7bt06xo0bF5Dw3H333axfv77DCQ/A7Kkj+PUFJxIbloBVH0Vl1iiqj/ZvdntTZDUqXtweN/tyeseVHiFE20jSI4QQQogW6XQKYwYnEWawovr01FVHt7i93uQhfsQ23KqDiroS3vxqO6t/ympzex6Ph4cffpgZM2aQl5cHQFxcHJ988glPPvkkJpOpQ+Np7N75U7li+hgSrMmE6SKoODgWW1FK0G3NEdUAOL11HCwox+fr8ZtlhBBtJEmPEEIIIVo1NWMgFoMVBR2OioRWt7fGVBI5MJMadyV2p417X/2a4gpbq+Wys7OZNm0ajz32GD6fD4Dp06ezfft2Lrroog6P41iKovDYjTM4/5ShJIanYFHCKTswgZrCprOz6c0OFJ0Pj89NebUDm8PV6f0RQnQNSXpCUFxcTGFhIcXFxT3dFRECiZt2Sey0SeKmTa3F7eyJJ6AAZl0YdZWJbaozZuAhTNGllNUVUVpdw+3Pfd7i1ZEVK1YwYcIEvvvuO6D+Ye+//OUvfP311wwY0HVTROv1Op767bmcNfEEkqz9CNNFUH4wg7KDowJu5VMUUBQVVVVRUXvFDG5yvGmTxK37SdITgsLCQvLz8yksLOzprogQSNy0S2KnTRI3bWotboP7xTIwKZowQzhuWzROe3irdep0CgkjtqMaHZTWHmXrgUKefX9Tk+1sNhs33HADV111FVVV9bO9DR48mA0bNnD//fd3ywxXJqOe5+84n/NOGUpieCpRhjhshekc3XEKLlskAKpXh6rWf3VSVegNN7fJ8aZNErfuJ0mPEEIIIdrkotOGE2GKQoee6oJBbSpjNLuJG7Ydp89BlbOc1z7dyuHCCv/6n376iYkTJ7Js2TL/sgULFvDzzz9z6qmndvYQWmQyGnhm4XncOnsSCRGJxJtS8NQkUPjzVIp3T6R070moPgWzLoy0pGh0SvMTOgghehdDT3dAS9LT01FVFUVOcpoicdMuiZ02Sdy0qS1x+9W543njs5+xGiKxF/fHm74fvbH1W7wi4stwpGRTfVRHuDGKR5atZem9c3j66ae5//77cbvd9dtFRPDCCy9w7bXX9tjnx6DXcfcVpzF8YDz/++Y6LJVhVDsrcJSb8OElTLFiNpo5bcwAYiNDez9QV5DjTZskbt1P3tMjhBBCiDZb+OxnfPrDXgrsR4gZvJvoATltKud168nfOg2zL5Z4JYL4gi/ZummDf/3JJ5/M22+/zdChLb8ktDvlFlXx8idb+OS7A9TU1uHz+dApCudMHsYdl5zCmMFJPd1FIY5L7ckdJOkRQgghRJtt2ZfP/Mfep8iej9tUQv9J62nrj9VVhamUb4hC3bEWn9PuX37PPffw2GOPdepU1J3F51M5WFDOtsyjHCmqpF9CJJNH9mdo/zj5lV6IHtKe3EFubxNCCCFEm00a2Z8RaQnUHrJTUleLoyIOa1x5k+08Xh/ZhZUApKfGoPNC3Xfb8f5Y7d8mOjaBle/+i7PPPrvb+h8qnU5h+IB4hg+IB5BbkoTQKEl6QuBy/TIff2/8NUoEJ3HTLomdNknctCmUuC2YmcG+nFL0TiM1hYOCJj2NOXPrKH23BHep+5c2UkcwcOZNTD719I51vJv1toRHjjdtkrh1P0l6QrB3717cbjdGo5Hx48f3dHdEG0nctEtip00SN20KJW6XnDmav733A1V10VRVuHE7LBjD6oD6KzwAXp8PfCpsqaNwcznUL0YxKphOPhE1/nRqfUae+WATD/9qWpeOrS+T402bJG7dTx6aEUIIIURILCYDs6eMIMocjU7VU5E93L8uu7CS7MJKcvdXwMoa+MHhT3hI1jPw9wNJnuVGVbxU1ZWzYs1uCkprgjckhBCdRK70hCA6Ohqv19stL0kTnUfipl0SO22SuGlTqHG7be7JfLB+L5GuWKpKvdTVZGGJrKl/a+ceF6yzQ8PdbApwsgVODsOUaAIcWJNzqDmqJ8oZw0sf/chjvz6rq4bWp8nxpk0St+4ns7cJIYQQol2eWvEdL328hXxbNvqooyQN+YGilUXU7q79ZaMoHUnzk7CmW4H69+AAuJ1GCn48i2hjAgNiU/n++V9jMctvsUKI1rUnd5CsQgghhBDt8ts5J5MQbSXaFEddpo0jT+YFJjyjzbAgGmu6FYNe5094AIxmN5b4QmzuKmpqnaxYu7sHRiCEOF5I0iOEEEKIdrFajNx4zhjqdvwH76ZP8Nnr72fTWXUkXpMMZ4eDqfnZzqL6HcGreqh123jnm53d1W0hxHFIriMLIYQQol02bdrEU/deT9WBA/5lxrR4+vLR26oAACAASURBVP8qEkOUgehWyluiqjCEV1PjsHIwv5xNe/I4ZfSAru20EOK4JElPCA4dOuSfXnDIkCE93R3RRhI37ZLYaZPETZtCiZvL5eKRRx5hyZIl+Hz1U7MpeiPmMTPwDj4B1bQecLbapqJAROoRKg9G4fa5WfrFNkl6QiTHmzZJ3LqfJD0hsNls/g+o0A6Jm3ZJ7LRJ4qZNbY3bjh07+NWvfsX27dv9yyZPnsywmTfyXXYt+bZsyg+PImnUNtryHs+IxAKqskdS7azg223ZFFfYSIqN6OhwjhtyvGmTxK37yTM9QgghRC+UX1LNwfxyCst6xztsvF4vS5YsYdKkSf6Ex2Aw8Nhjj7Fx40ae+uPVRFnDiDUlUleWQnVh267Y6A0q1sQ87J4aXF4vy77Y3nohIYQIkUxZHYKGS/hAr+ubaJ7ETbskdtokceuY4go7D7z+Det35OD77z/RQ/vHcuX0DK4+eyxGY9e816OluGVmZnLdddfx/fff+5dlZGTw5ptvcuKJJ/qX/evrnTy8dA3FtUdxqFWkTNiIOdzeatuu2jAKt04j1pzEmIFprP7bdZ0wouODHG/aJHHrGJmyuovpdDr/n9AOiZt2Sey0SeLWfj6fyh9e+JLVPx+iqLaAAtsRiuz5bM/K4X/fWsech95hd1Zxl7QdLG4+n48XXniBCRMm+BMenU7Hvffey5YtWwISHoD5Z4/lvMlDSQhLQq+aKd17Il5P6/e4mawODOFVODx2couqyC+p7tzB9WFyvGmTxK37yZ4WQggheokvNh9ky/58SuuO4lDL0ccdwmMupLSukEJbDruOFHDFI+/xz693dHlfcnNzOffcc1m4cCG1tfXv3hkyZAjr169nyZIlmM3moOUev3kmg5JjSbCk4HFEUn54dJvas8SW4PQ6UIGvtx7urGEIIQQgSY8QQgjRa6zdlo3DU0edx0HUCdtIGrmTfhM3kpixCZ+5gqO1uZTaylm87Fue//fmLumDqqosX76cjIwMvv76a//y2267je3btzNlypQWy0dYzTyz8Dwiw8KJMcVTWzSQmuKUVtsNiy1FxYfT42DDzpwOj0MIIRqT2dtCUFZWhs/nQ6fTER8f39PdEW0kcdMuiZ02Sdzab3d2MS6vExQf1rgylP9Of2aNrcB84gbKDo6hokTFq3p5duUPqKrK7Zec0iltl5WVUVBQwB//+Ee++uor//L+/fuzdOlSZs36/+y9eXwkVb3//a6q3tPZ09kny8xkktnZVxfgIgjI44obXLzCjyuioP5QBrmPAgNcARFZBL0I6KNyvSggAoJehQF0hGGZNZlJJutk37o73em9u6qeP0J60kknk8xMlmLO+/WaV6BOnW+dcz5Vp+tb55zv+cisbW1YUcQ3P30aP/yfrUQSYbwt67E5fZgd4Wnz2DJHQFaJJELUdwwdUV2OJcTzZkyEbguPcHrmQHd3dzK8oLhBjYPQzbgI7YyJ0O3w8YdiqHoC2RxFUXTg4HoYxaThqt2DxxzD3wvoOg88vQ2zonD1x086ouvqus7DDz/MD3/4w5TFwf/6r//KAw88QE5Ozpxt/p+LjufNvd28ukulLxhlcN8JFK/fhmJJpD1fVsDs9BENZjE8EmTYF6QgO+Ow63SsIJ43YyJ0W3jmPL1tdHSUG264gfPOOw+Xy4UkSdxyyy0p56iqyr333stHP/pRysvLcTgcrF69mhtvvJGRkZGjVXaBQCAQCN5XKPJ7To6efvG/JEHe8iacpe34Ex5GIl7uf2YbW+sPfzpYd3c3F110Ed///veTDk9xcTHPPvssv/rVrw7L4YGxhdr3XnM+pfnZuGwlqKFs+utPRo1PH33OZAuS0Macos5BEcxAIBAcPebs9Ljdbh555BGi0Sif+MQn0p4TDoe55ZZbqKys5L777uPFF1/kqquu4pFHHuHMM88kHJ5+eHspU15eTmVlJeXlYrdoIyF0My5CO2MidDt8LCYFWZLRNQVtmg0lxh2fjKIufHE3o+EANz7yMh5/aE7X0nWdxx9/nLVr1/LSSy8lj19yySU0NDTw8Y9//EiqAkBOpo2ffetjFGRnU2gvRQ3mMtBwImoi/euHyRpB08ecnm7h9MwK8bwZE6HbwjPn6W2VlZV4vV4kSWJ4eJhHH310yjl2u5329vaU4bqzzjqLiooKLrnkEp5++mkuu+yyIyv5IiCGH42J0M24CO2MidDt8CnJd9LQbUZXTagxM2Z7+qlgkgT5K/YRHc3BHTJhGbKy6ZGX+a//+zFk+dAhoru6urjqqqv4y1/+cvDaJSX813/9FxdffPFRqw/AuuWFPPrti7ni7ufQdZ2hURjYcwqFa9/BNGmqm6zE0Rjbv2QkEDmq5Xi/Ip43YyJ0W3jmPNIjSVJyYeV0KIqSVsxTTjkFGOtsBQKBQCAQpLKyLA+zbAEgFsia8VxJ0XDV7USTIwyH+9myo53HXtwxYx5d13n00UdZu3ZtisPzpS99iYaGhqPu8IxzwqpSfvqti8jLzMZlLyURyKNvxwcI+7JTzlMTFmRpbPpbQbZjXsoiEAiOTRY0kMErr7wCwNq1aw95bkNDA5WVlWRlHez0o9EojY2NAOTm5lJRUZGSp7m5ObmXwMaNG1PShoeH6enpAaCiooLc3Nxkmqqq1NfXA2O7uS5fvjwlb3t7O36/P1l2k+lgs42MjHDgwAEASktLcblcKXl3796NruvY7XZWrVqVktbV1YXH4wGgtrYWm82WTAsEArS2tgJQWFhISUlJSt69e/cmF8CtWZO6B0JfXx+Dg2Ob161YsQKn05lMi0QiNDU1AZCXl8eyZctS8u7fv59wOIwkSWzYsCElbWhoiN7eXmBsxG/iPO9EIkFDQwMAWVlZVFdXp+Rta2tLzhVft24dinJwTrfX66Wzc2w+ellZGQUFBSl5d+3aBYDD4aCmpiYlrbOzE6/XC0BdXV3KvhF+v5/29nYAioqKKC5ODZna0NBAIpHAarVSV1eXktbb28vQ0Fj0oJUrV5KRcXAxbSgUorm5GRj7UjN5aLqpqYlIJIKiKKxbty4lbXBwkL6+PgCqqqrIzj74gx+Lxdi3bx8A2dnZVFVVpeRtbW0lEAgAsH79+pQNzdxuN93d3cDYkPnEjw6aprFnzx4AnE4nK1asSLHb0dGBz+cDYPXq1VgslmSaz+ejo6MDGPsKXFhYmJK3vr4eVVWx2WzU1tampHV3d+N2uwGoqanB4Tj4AhMMBmlpaQHA5XJRWlqakrexsZFoNIrJZJrSX/T39zMwMABAdXW16CMQfcT7qY+odtnR4joSEtHRLHB5kmm6rhOLxYCx9TJmsxlLRpDcFXvxNK/HG3Rz9xOvkiWNcskFH5zSR7z99tvceuutvPnmm8njpaWl/OxnP6OiooLOzk48Hs+89RGnr63lse/8P3zl3hcwySYGg70M7D4VR1EruRWdmKxxoiMFmCQTmq7jG+5h166Q6CNEHwGIPmIc8R4xxvhzOhcWzOnp6enhxhtv5KSTTuJjH/vYIc9PJBLoeuqEZl3XicfjyfR0ecbTJ6NpWjJN07Qp6bO1q6pqyg66E+2qqprWrq7rmM3mKWmqqibzTq7rbOxOV9eJdifXdWIbprM7Xtd0o3mztbtY2hzqfhkPDTnRbiKRSLsb8kzaHKoNx7VJlzaT3Yl1navms23DdPknlmkyh6prLBZD07SUH590dg+3DXVdT9ZnXKfZ2l0q9+Gx2keoqpryzC1FbWZzHy50H1FbloMEmLAQG81D19tT2nr8WjoHr+ks6iE8ks/ooIQpYuHHf6znorNPw+mwJvP88pe/5OabbyYYDCbzffnLX+bee+8lKyuL7du3J8s2ua88mn3EyXVlPH3rZ7n2gZfY0wreyDCh/hrCgyuRZBVdNZFvzaEkz8lyl2PadprYR0zmWO0jJudd6n2E0d4j5quPSFcm8R4x1W66NpwrC+L0eDweLrzwQnRd58knn0x7c0zGZDJNeWAkSUo+9BO/kkzMk65TgINfxcb/ezKzsRuPx9mzZw9mszn5BWii3XSCmc1mdF1Pa1dRlGTeyXWdjd2Jf6ezO7muE9swnd3xuqbrrGZrdzG0GS9DujLF43H6+/txu90pX+7G63moNpzpPpxOG1VV06bNZHdiXaeze6RteKi6TuZQdbVYLKiqOi9tON4Bb9++PeWZm63dpXIfHot9RDwep729ne7u7qRuS1Gb2dyHC91HLCvMJi/TSiDhwO93EYuasdoOvhSNX0uaEMpakqBgZQM9/mz8ERM9HguPvbiDb3zmNFpaWrjqqqt49dVXk+eXlJTw2GOPccEFFwBjLzjjugUCAfbs2ZPSVx7tPqK6JJdnbv0s1//kBV7YBrFEDlHCaHoCq9WO05LJv52/HpvNOmMbapo25+dmKd6HR9pHjNPc3Mxxxx03J7sT/062K94j5rePGMfj8UwZkRHvEVPtztSGs0XSD8dVeo/h4WFcLhc333zzlLDV43i9Xs4991wOHDjAK6+8MmWoE8Y63In7AsDY8PBsnKOFZNeuXcmh4MnD3oKli9DNuAjtjInQ7cj4zyf+zqN/epfuQBuZVfXkLZvdOtiwN4/B+lPIMbtYlufigtIhfnT3D4hEDgYEuPLKK/nRj36UMiVmnMXQ7UD/CA89+zZvNfbgC0bIzrDxlYtP4gv/su7QmQWAeN6MitDtyDgc32FeR3rGHZ729nZefvnltA6PkXA6nckbVGAchG7GRWhnTIRuR8ZnP7yGX/55JzaTg/BQOXp556y+atpzPdjyBhlp9+Db8nO2e7uTaZWVlTzyyCOcd9550+ZfDN0qi3O4++qPAAenqxzOF9xjGfG8GROh28Izb07PuMPT1tbGX//6V44//vj5utSCMXnhlsAYCN2Mi9DOmAjdjoyV5fmsKs8n2DbKUDBIJODAnjl1f7uEqtHRN7bhd1VJDrIGUusW4luHYYIDcd1113H77benLEZPx2LrJpydw2OxdRMcHkK3heewnJ6XXnqJYDCYHFbau3cvTz31FAAXXnghkiRx/vnns2PHDu677z4SiURKtBiXyyXEFggEAoFgGj75wToaO4eQJYXAYBn2zJYZz4+0h3E/M0x8+OBiYnNWMR+/8gZ+/KNvCodCIBAc8xzWmp6qqqpkeMXJjIf2mxxqcCJf+tKX+OUvf5n8f6Os6REIBAKBYCHw+MOcee3jDAT6CEn9lJ70Kooy5rgk1LHISqqm0dXpg3+GYE/0YGZFQll5Es5V/0JpXjm/u/kS1lUXpruMQCAQGJIFW9MzHm97Jo4gPoJAIBAIBMc0eVl2Tltdxsu7QgSCPgLDRWQXje2bMj6ljbYYbAlCcMLvbbHCsi+WEgwWEegNEYpE+Nlz7/DgdReI0R6BQHBMs6Cbkxqdjo6OZAjByeEFBUsXoZtxEdoZE6Hb0eFLHz2Of9R3YVXsjHbV4HQNoMgShDR4LQTNsYMnm4HTHbDBirXYiinWRqC/An90hK31nfR7ApTkZ854PaGbMRG6GROh28IjnJ454PP5RKQNAyJ0My5CO2MidDs6fHhjJWurXERawgyEwowOFiEdaEb+kx8tMmHzwAozJZ8txJp/cCd5xRLDljdIeNiKPxjlpW0tXHHhzAGFhG7GROhmTIRuC49YNCMQCAQCwRJEkiSu/+zp2Ex2zMEQ7l+1MPT0UNLhke0yfCQDPu7Emm/FpMiYlIM/687CHlTihOMh/vxWS3ItkEAgEByLHNHmpEcLowQyiMUOTiWwWCyLWBLBXBC6GRehnTERuh09QqEQJ3z0X2na+kfQ1OTxzBMyybkgj673fjurSnJSHB4AXZPofuscrGoepdmlPLP5c6yudE17LaGbMRG6GROh25Gx5DYnfb8hbkpjInQzLkI7YyJ0Ozq8/PLLXH311bS0TAhXnZFF4SVZZK2xAbAyO2/a/JKsk+HqJdBrIxKN88etTTM6PUI3YyJ0MyZCt4VnaQ2lCAQCgUBwjDM0NMTll1/Oueeem3R4ZMVE9tpzMZ91GRHzxlnbchb2oqMSigfYsqOdcDR+6EwCgUDwPkQ4PQKBQCAQLAF0XecXv/gFdXV1/PrXv04eP/PMM/nbq1spO/mTZNsLCfdXE3Dnzsqm2enD5AgQSgRo7fWyq6V/voovEAgESxrh9MwBn8/HyMgIPp9vsYsimANCN+MitDMmQre509jYyNlnn80VV1yBx+MBICcnh5///Oe8/vrrnP2BU7j64hPJtuRile14mo8jFjl01CdJAkf+ADE9gqqqvLO/b9pzhW7GROhmTIRuC49Y0zMHOjo6kuEFN26c/fQCweIidDMuQjtjInSbPeFwmDvvvJM777wzZWHzF7/4Re69916KioqSx772iVP4Z30Xbzaq9AVjuJs3ULT2HWR55k1HbZk+/GjE1Rj7DgxNe57QzZgI3YyJ0G3hEU6PQCAQCI5JWro9/PaVPQz7QphMCh9cX8H5J63AbluYfTNefPFFrr32Wtra2pLHli9fzk9/+lPOO++8KefLssSD113IBTc+QUwtZmhExdtVTX5lx4zXMTvHviTH1Cgd/T6C4RgZdrGIWiAQHFsIp2cOlJSUJHfPFRgHoZtxEdoZEyPo9ouXdnLXb/9BLBEnrsWRJZnn/tHIZoeVqz52Av/nwhMwm+en/J2dnXzzm9/kD3/4Q/KYyWTi29/+Nt/73vdwOBzT5i3IcXDP1R/hqh89TySRw2hXLbZsDxk5/mnzKJYosilOXIsxNBJkdBqnxwi6CaYidDMmQreFR+zTIxAIBIJjijf3dvPlu/6IJ+zGGxkGxn4GFclMljmHTGsOdRUFPHDtR1leOn1I6LkSi8X48Y9/zObNmwmFQsnjZ511Fg899BBr1qyZta07fv06v/jzTvqCXagmL0Ub3sRij057fu/2M1FCxZRklfHSXZexvHR2gRAEAoFgKXI4voPwKgQCgUBwTPHj379JIBbEGxnGVtRO4ca/k1/3LubcbryxIfoCnexp7+Pztz3N2/t6jso1X331VY477jhuvPHGpMNTVFTEb37zG1555ZU5OTwAm774AdZVF1LoKEGKZzK451RiYeu050uyhg6omo62+N86BQKBYMERTo9AIBAIjhkGvUF2tw0QiPlQbKPkr9iHPSuI0zVE0doduNa+jWr2MRDqos/t4d/vfZ4tO9oP+3r9/f1cdtllnH322ezbtw8AWZa59tpraWxs5NJLL0WSZg5EkA6TIvOzb11EeUEuRY5yiGWNOT4h2wy5dNB1VFU7zNoIBAKBcRFOj0AgEAiOGZq6hkmoGhE1hDV3AJOS6nA48tyUbPwnsmOEwUgvAyNern/4f2loH5zTdRKJBA8++CC1tbU88cQTyeOnnHIKb7/9Ng888AA5OTlHVJfi/Ez+53ufZpkr7z3HJ5v+3WcQdBeknKfrkAg5UTCTl+XAMk9rlQQCgWApIwIZzIH6+npisRgWi4V169YtdnEEs0ToZlyEdsZkKes2NBJE13U0XUWxhdKeY7LFKNnwFgMNJ+IeBZPfxKZH/sZv/99Pk5kx/RSycbZt28ZXv/pVduzYkTyWm5vLXXfdxZVXXnlU16uWubL4n+99mkvveAZ5UGYo1Mfw3pMIFnaTU96OJSNIaLAMTVWwmmwsK8wix5l+NGgp6yaYHqGbMRG6LTxipGcOqKqKpmmoqrrYRRHMAaGbcRHaGZOlrJs/FENnbH2LbEpMe55sjlO4ZjuSJYw7MsC+A4Ns/vVraNr062EGBwe58sorOe2001IcniuuuIKmpiauuuqqeQnQU+bK4pnNn+Pk2nKKMsrJsRQQGaygb/sH6XrjXIb3r8ci2bGbHZy+dhlZjvSO21LWTTA9QjdjInRbeITTMwdsNlvyn8A4CN2Mi9DOmCxl3TJsZqT3fvq0xMyTHRRLDFftTuJEcYeG+OM/mnhyS/2U8+LxOPfffz+rVq3i8ccfTx7fsGEDW7du5bHHHsPlch3dikwiL8vOb7/3aa7/7BkUZrooc1aTaynEruWTqeSRby3khNoyPnvWWhQl/U//UtZNMD1CN2MidFt4RMhqgUAgEBwzbN3Tyb/d9Ue6R9uwlu7Dtbz1kHlGOlfgO1BDnrmIkrwCfn3Tp1hXXQjAli1buPbaa2loaEien52dza233srXvvY1TKaFn0Xe6x7lV3/exV/fbSUYiaPIEqetKefLFxzP2irXYQVOEAgEgqXE4fgOYk2PQCAQCI4ZivOcyJKEIptQI9NvAjqR7GWtRHy5eEdkLH4bd/12Kzd/7jhu+u4mfv/736ece8UVV/CDH/yAwsLC+Sj+rCjNz+TGSz/A9Z87nWAkjqpqZDqsIoCBQCA4phFOj0AgEAiOGcpcWVjMMhbZRmg0D1XVUZSZRz4kCVy1u+l990N4gwO8+OQWfr/5FaLRSPKck08+mZ/85Ceccsop812FWWM2KeQ4haMjEAgEIJwegUAgEBxD2CwmTqgpwbtrlEDITiSQSUZ24JD5ZHMUa/wN/FvaIeRPHne5XNx5553827/9m5iSLRAIBEsY4fTMge7ublRVRVEUysvLF7s4glkidDMuQjtjstR1O//kFWyt70KWFMLuwrROT0LV6OgbAaDM5MD7Jw+hpgkhriWZiz59Kb/5+ZHvt7NUWOq6CdIjdDMmQreFR3yWmgNut5uhoSHcbvdiF0UwB4RuxkVoZ0yWum7nnrgCRZaxKQ4i3mK06eL5RHXYGqLn/u4Uh0fKL8P1L9diWX0RVnvGApV6/lnqugnSI3QzJkK3hUc4PQKBQCA4pijMzaCuogCH2YkayiIaPhgyNqFqxOMqvm0++NUIvBuB97bRULIVir5YguXDFxB2WNndOsCrOw8sUi0EAoFAMBfE9LY5UFNTg67rItynwRC6GRehnTExgm7nnric+o5+JEkiOFiCvaoDgI63h+D1EAxP2DBQAU6woZ5kJ7M6A727A2+7nWgswvNvNHH+ySuQ5aVb19liBN0EUxG6GROh28IjnJ454HDMLrypYGkhdDMuQjtjYgTdPn5mLQ89+xYOUyah/mrCjhZG/jwE9cHUE1da4AN2yDoYBS2jsBdvRx2hRIDdrQMM+0IU5hp/mpsRdBNMRehmTIRuC49wegQCgUBwzFFRlM1Zx1Xx4hs+/Du30/PsAdAOru0xl1iIn2GFMjPLirJQJkRmUywxrJkjREdt9LlH2dnSz3knr1iMaggEAoFglog1PQKBQCA45lBVlbJ4C70v3IXW8m7S4VGcCoWXFFL69TIoM48dk2VMyti/cRz5A8T0KPFEnJe3t6FPFwxBIBAIBEsCMdIzB4LBYHL+ZUaG8acyHCsI3YyL0M6YLHXdXn/9db75zW+yY8eOgwdlGevGCso+KSPbZBKqNqMNe/4g3vZawokgO1v6GQlEyM20z3PJ55elrpsgPUI3YyJ0W3iE0zMHWlpaiMfjmM1mNm7cuNjFEcwSoZtxEdoZk6WqW1tbG5s2beKpp55KOe6sOA559RlE7BoJ6TUsxDEpMivL86a1ZbYHMduDRCIO2vq87O9yc+oaY++1sVR1E8yM0M2YCN0Wnjk7PaOjo9x2223s3LmTHTt2MDw8zM0338wtt9wy5dzt27dzww038Oabb2IymTjnnHO45557WL58+dEou0AgeJ/x+UfeYMAfTf5/NBpB10GSwPpXb/J4UZaV//n30xejiAID4vF4uOOOO3jwwQeJx+PJ4xs3buS+++7jhX0xnvl7A73BA7j3r6do7buzisZmyx0m1JtNIqGy78Cw4Z0egUAgeD8zZ6fH7XbzyCOPsHHjRj7xiU/w6KOPpj2vsbGRs846i+OOO47f/e53RCIRvv/97/PBD36QnTt34nK5jrjwC43L5UruniswDkI34zDgj9I+HEyfODrNccGSY6k8c9FolIcffpjbbrsNr/eg01xYWMgdd9zBl7/8ZRRFYe1xQV7bdYCoWsTQiIq3q4r8ykPvv2O2hdFQ0TSNPvfofFZlQVgqugnmhtDNmAjdFp45Oz2VlZV4vV4kSWJ4eHhap+f73/8+VquVF154gaysLABOPPFEampquOeee7jrrruOrOSLQGlp6WIXQXAYCN0EgoVlsZ85Xdd5+umn2bRpE21tbcnjNpuN66+/nhtuuCH5uwTgysngh1/5CP9+7/NE1FxGu+qwZXvJyPHPeB3FGkFHR9VUBkaCht9zY7F1ExweQjdjInRbeOYcvU2SpEN26olEghdeeIFPf/rTKT8slZWVnH322fzhD3+Ye0kFAoFAIDgEb7zxBmeeeSaXXHJJ0uGRJInLL7+c/fv3c/vtt6f8Lo1z1vFVXHHB8eRaC7BIdjxNJxCPzvxdUDaNTZXTdJVILHHI4AcCgUAgWDzmJZBBa2sr4XCYDRs2TEnbsGEDf/3rX4lEIthstmltNDQ0UFlZmfLjFI1GaWxsBCA3N5eKioqUPM3NzYRCIYApi8KGh4fp6ekBoKKigtzc3GSaqqrU19cDkJmZOWXNUXt7O37/2Be/tWvXYjIdbLaRkREOHBibBlFaWjpl2t7u3bvRdR273c6qVatS0rq6uvB4PADU1tamtEcgEKC1tRUYm4pRUlKSknfv3r3JBXBr1qxJSevr62NwcBCAFStW4HQ6k2mRSISmpiYA8vLyWLZsWUre/fv3Ew6HkSRpin5DQ0P09vYCYw5sTk5OMi2RSNDQ0ABAVlYW1dXVKXnb2toYHR2b/rFu3bqU4Vyv10tnZycAZWVlFBQUpOTdtWsXMLaRV01NTUpaZ2dnctpKXV0dVqs1meb3+2lvbwegqKiI4uLilLwNDQ0kEgmsVit1dXUpab29vQwNDQGwcuXKlMgqoVCI5uZmAPLz8ykvT53H39TURCQSQVEU1q1bl5I2ODhIX18fAFVVVWRnZyfTYrEY+/btAyA7O5uqqqqUvK2trQQCAQDWr1+PPGHfGhdPfAAAIABJREFUELfbTXd3NwDl5eXk5+cn0zRNY8+ePQA4nU5WrEjdT6SjowOfzwfA6tWrsVgsyTSfz0dHRwcAJSUlFBYWpuStr69HVVVsNhu1tbUpad3d3bjdbmBs5+mJG7EFg0FaWlqAsSH+uX7xikYj7Nq1i+rqatFHsPT6CFXT0a3ZDAdUOvpHCIRjLCvMwqH5KM3LIDcn+6j3EV1dXTz88MO89NJLKWmnn3461113HatXr55y/07uI77zuTN4d38f7+xP0BeMM7B3I/mrtqGYtZTnAsb6vGhES4aqNpsOPo+ijzjIfPURjY2NRKNRTCYTa9euTUnr7+9nYGAAQPQRS7SPAPEeIfqIMQ63jxh/TufCvDg94wXMy5sa+SYvLw9d1/F6vVMewIkkEokp+x7oup5chJpIJNLmmbhIdSKapiXTNG3q17jZ2p1cpol2VVVNa1fXdcxm85Q0VVWPyO50dZ1od3JdJ7ZhOrvjdU03mjdbu0tFm0PVNR6Pk0gkUh76cWbSZjZ24/F42rSZ7I7nPZTddMy2DdPln1imyRyqrrFYDE3T0s5JPpI2PBS6fvDZms7uUrkPj7U+IhiOsKPNw7sHWvhHQw/R2Fh7SZKEWYbjl+dx2b+spqqqKsXG4Wrj8Xi4++67+d3vfpeizerVq/nhD39IXV0dXq/3kPfL2Nx6mZ9cdwEfu+m3xLUSBkdVhhtPJ792G5N8HnRdR42NvRzJkkKWw4rZpMyqDUUfMdXu4faz6dpotnZFHyHeIybbFe8Rxuoj5sq8hqyeaRrcoabImUymKedIkpR86Cd+JZmYJ12nACDLcjIt3c05G7uJRIJ9+/ZhsViSHv1Eu+kEM5vN6Lqe1q6iKMm8k+s6G7sT/05nd3JdJ7ZhOrvjdU2nz2ztLoY242VIV6ZEIsHg4CCjo6MpX2LG63moNpzpPpxOm+kWJ85kd2Jdp7N7pG14qLpO5lB1tVgsqKp61NvwUEgSae/TpXgfHkt9hCzLNPaM8uy2A+xqGyJCiIQcRdM1ZEyYdDN/3xtlZ8cILcMa137qlKSjMFdtIpFIMkjByMhI8tzCwkI2b97MlVdeiclkorOzc073YVGek4e+cSFX3fMciXgxnqCEe++HkOp2Yc8aTckb8xWjYEaRFaqKc2a0O5Gl2kckEglCoRCNjY0pfeVS7CPMZjOaps35uXk/9hGSJKHrOu3t7SkjNkuxjzDqe8R42dPZPdz3iHHdRkZGqKysnGJ3KfYRE/9OV6bJzGcfMVck/Qi2kR4eHsblck0JWd3U1ERdXR0PPfQQ11xzTUqe73znO/zoRz8iFAolh2E1TUsOWY6TmZmZttEXk127domY6gZE6GYczr7n1emjt02guiCDLd8+a/4LJJgTfe5RfvrHt/mvZ99gVPeSkCI4i/oxWcPEAk7CIy7QFDJNueTY8zj7+Gp+9NWPkJUx/VTnyaiqyhNPPMH3vve95HQWALvdngxSkJmZecR12d3azxV3P8ew389gqI8EMRxFnWSVdGJxhAgNl+Dev54McqgqLONX3/0U65YXHtrwEkb0lcZE6GZMhG5HxuH4DvMy0rNixQrsdnty/t9E9uzZw8qVK2dcz7NUMZlM035tESxdhG4CwcLQ1uvlL2+3ENXCJOQIOSvfIbvEnUxPRK14O1bhH9SIBSO8vF3j//wwwhP/8SnM5plH/HRd58UXX+TGG29Mrp2Ag0EKbr/99inz4o+EDSuKeerWz3LVPc9j6rMwEnEz2i8T6j+4BsQi2cm05nDOCcupKMqewZoxEH2lMRG6GROh28IzLy1tMpm4+OKLeeaZZ7j77ruTX906OzvZsmUL3/rWt+bjsvPO5MWSAmMgdBMI5h9d12nu9tDn9pNQotiyfCkOD4DJGsVVu4fRbA+e1rUMBlW2N8t87xdbuPPfz53W9ptvvsmmTZt4/fXXU45fcMEF/OAHP5i3r6RVxTk8f8cXuO/pN/n1/+4iO5ZLKB4kocZRJBM2k4OTV5dz9cUnkpVhPbTBJY7oK42J0M2YCN0WnsNyel566SWCwWByWGnv3r089dRTAFx44YU4HA5uvfVWTj75ZD72sY9x4403JjcnLSgo4Prrrz96NRAIBO8birJm9+I42/MEC0coEqej34umaiSIkZ07NO25mcU9KJYwQ3tPwR0a4OnXYHVlAV86/7iU8xobG7npppumbHNwyimncNddd3HWWWfNR1VSsFlN3PjFD3Dpuev53at7+fvuA4SjcawWE2esXcbnz15LVUnuoQ0JBAKBYFE5rDU9VVVVyfCKk2lvb0+GyHv33XfZtGkTb7zxBiaTiXPOOYd77rlnSqg7o6zpEQgEAkF6RgIRvv/4Fp56dSfDai+u1Ttw5A/MnKerEl/HanItLvKd+Tz+nY9z2tpyenp6uPXWW3n88cdTov2sWrWK//zP/+RTn/rUom4CGo0lkGUJkyIbejNSgUAgMCoLtqZnPN72oTjxxBP529/+djiXEAgEAoGBkABV09DRQQdJPnQo8uzyA8SCWXiHJMxhK9+6/1k+kN3FQw89SDgcTp5XUlLCLbfcwpe//OVpIwQtJFaLmIMvEAgERkP03HOgv78/GUJw8gZVgqWL0M24CO2MgyxLWMwKkjT2lS0RG9v/YqZFupIEBSvr6fXbGKjfSV/Lu7wZO7jhXFZWFps2beIb3/hGysZ+gvlBPG/GROhmTIRuC49weubAwMBAMryguEGNg9DNuAjtjIPNYsJiUlAkZWwzuogZi6qmOD2aptPWO7bz+fLSXCQNRt/yEfvb79ECBzcNtFgsfO1rX+Omm26asrO6YP4Qz5sxEboZE6HbwiOcHoFAIBAcMWaTwppKF4qioGAmNlpARnFH+pM1nbaX+zG9EyXhTd0h3Vl1Etf+3xv5z2s/Pf+FFggEAsExg3B65kB1dTW6rouFqwZD6GZchHbG4oSaEjLsVixhG7FAISbT2PobTRuLl6OqGjTH4M0QeDUmujv2uiziRRdhL6jjf+vd3BxLiLUzC4x43oyJ0M2YCN0WHvGLMgeysrIWuwiCw0DoZlyEdsaiMDeDmvJ8hnxuIvEAajgbxTlKW48HDsThjTAMTQpwUGGi9OIiHJV2+hvijHpHGAnk8Nw/m7jkLLGPxUIinjdjInQzJkK3hUfEhBYIBALBUSE/28Gq8nysJjsgERnJJ9wahqdG4blAqsNTYoJPZcInsuhVxiK1OUsOoOpxYlqU13al3xZBIBAIBILDQYz0CAQCgeCoYFJkTq4r5anXGlAGPAz/bi9af2/qSS4FTrdDpXksfNsE7NlekFXC8SDb9/eJqR8CgUAgOGoIp2cORKPR5I+w1Sp2hDcKQjfjIrQzHnmSj9G3fkWkbUfKcbPLTM5HchnKjyednaqSHOQJTo2igDnTSySQyZAvxIF+H1UlOQta/mMZ8bwZE6GbMRG6LTzC6ZkDjY2NyfCCGzduXOziCGaJ0M24CO2Mw+7du7nlllv4wx/+kHJcysig4KIMsk7IRAeG3gtZDSBLErKcOpJjyx4m4C9E13W27GznyyXHL0TxBYjnzagI3YyJ0G3hEWt6BAKBQHDY1NfX85nPfIaNGzemODwmRzb29RegnHU5psoaJHnMwVlemjujPWuOG13XiKkRtu/vm+/iCwQCgeAYQYz0zIHc3NxD7jAuWHoI3YyL0G7psnfvXm699VZ+//vfo+t68nhxcTFXX3018cKN/OqVFtyxAUY66rDnupFNCWRZYmV53rR2zbaxoAaqnsAXis57PQQHEc+bMRG6GROh28IjWnoOVFRULHYRBIfB+023SCyBPxglGImhajoJVUNVNTRdx2xSsFlMWM0KVrMJp92CxawsdpEPm/ebdu8H9u3bx+bNm3nyySdTnJ2ioiJuvPFGvvKVr2C323H7QrzTHqC+XWUoEmOo8TgK174zOXbBFCR5LMKbputEY4mZTxYcVcTzZkyEbsZE6LbwCKdHIFjijIai9HsCuP1hfIEIscR7L4WajqqpaJqGpqrouo5iMmE2mVPWSWTYLORl2cl12sjPduC0WxarKoKjhK7raJqOoizcDOWmpiY2b97Mb3/72xRnp7CwkE2bNnH11VfjcDiSx/OzHXz/8g/x1R//ifhIDK9XY+RADblVzTNeZ9y2JJES5EAgEAgEgiNBOD0CwRIkGkvQNeSna9BHIBxDVVX8fj+hUJhQKEgwGCIWm37qj2IyYTGbcTgcOJ1OBp2ZOBx2JEkiy2GlzJVFaX4mDpt5AWslOBLC0ThtvV76PQHCsQS6rmOzmMhx2qgozKYwN2Newjvv37+f22+/nSeeeAJN05LHXS4XN9xwA1/96lfJyMhIm/eMdRV85/NncOv/9zpxNYq/awWWDD8ZroFprxcPj9kyyWaKcp1HtzICgUAgOGYRTo9AsISIxVVaez20940QSyQY8XoZHnbjH/WjaxomRcZhUchzyNhzHJhkCfm9L+KSBAlNJ67qxBMacVUjGPTh8XjQdR1ZVsjKyiQ/Px9vIMy+A0PkZdqpKs6htCBT7IeyhBnwBPjHnk5e29XBvvY+BkeCmBWZ/Cw7x68q46TVy8jLdLB+eSGunPQOyFxpaGjgjjvu4Mknn0xxdvLz87nhhhu45pprcDoP7ZR84Zz17O/y8MTfNOLBOMP7N6Kp9WQW9045V9d1Ir48JEnCLFvZsKLoqNRFIBAIBALh9MyB5ubm5KKzmpqaxS6OYJYYQbeEqtHW66W110M0FmdgYIC+/n7URAKnzcSyPCu5DjNW89ynM2m6TiiqMhpR8QYDtLaOIMsKubk5+ApceEbDNHW5WVmWR7kra0oI4cXECNrNN/2eAE9uqefnz7+DxzdKTI+ikUBConPYzO62QZ58pZ7zTl6BP1hHbUUBtcsKDlvHnTt3cvvtt/P000+nHM/Ly+Pb3/42X//618nMzJzRxmTdvnvpB2jv8/LPBp2hUD+e5g1E/DnkVTehmNVkvmhUIdRfjd3kxKIofGC9mPO+kIjnzZgI3YyJ0G3hEU7PHAiFQsmY6gLjsNR1GwmMheYdDUUZHBygt7cPVU1QlGWhMNuO7QgDEciShNNmwmkzUZJjJRrXcAdiuEdHaHK7cWRkUFpSSjASY3+3m1Xl+SwrzFoSIz9LXbv5JhZXeW5rEw8/+xaeUS8B3YuOhqSo6JoMuoQsKURjGTy3tZEdzX1c+bFT8AWjnFJXNifH5+233+a2227j+eefTzleUFDA9ddfzzXXXENWVtasbE3WzW418/C3LuI7P/srf3tXxhfx4BuQCA+XYi/swprpRVVlQv3VEMskJyOf09cuY9Wy/Nk3luCIOdafN6MidDMmQreFRzg9AsEioes6rb1eGjuHGQ0EaG1tJRaNUpBppjQn87BGdWaD1SxTmmujNNeGP5yg1xuhpaUZu91OaWkp4WiczkEf66sLyXba5qUMgtmxv8vNb/66C2/Ah193Y8seJnfFPkz2ACAR8+cQHCwnOFhGjDAdgwnueuJVvv35D+G0W1hXXXjIa2zdupXbbruNv/zlLynHi4uL+c53vsNXvvKVadfszIVMh5WHv3kRDz37Fj997h0yoln4ox5C/TZCfQlAwqJYKXAUUpKbw/e/9OEjvqZAIBAIBONI+sQwPIuEpmmMjo6mHMvMzESWxd6pgvcnCVXjnaZeBr0B+vr76enpwWGWWV5ox25Z+BDTgUiCXm+UkVAcZ2YmVZWVZGRkUF2cQ21FAaYFjBImGEPXdX745D95+A/bGIz0IGe4Kd7wBpKiTTk3NpqNp3kD8VAmWVI+ec4sbrz0w/zLictZVpid1varr77K5s2befXVV1PSysvL2bRpE1deeSV2u31e6tbc7eb+p7bxt+1tqKqGqqtIkoQiKywvyeXea85nTZVrXq4tEAgEAuNzOL6DcHoEggUmFlfZtq+b4ZEgLS3N+P3+90ZerIseotcfTtAxFCaa0CgqLqasrIwMm4Xja0ooyHYc2oDgqOEdDfO1+17klR2NeBL9FK59F3ve0LTna6rMUMMpxP35ZEn5lBXkc8MXPshHT60h570RO13X+ctf/sLtt9/O1q1bU/JXVVXx3e9+ly996UtYrdZ5rds4wyMh3tjbRVOXm+wMK6vK8/nA+ooFDcUtEAgEAuNxOL6DmN4mECwgkViCN/d24/EHaWpsJBoJU1fqJMu+NB7FLLuJdcuc9I9E6e3vx+P2UF1dzRuxBDXl+dQuy18Sa32OBfzBKC29HqJaGFnRsOW4ZzxfVjRcq99lYM9p+EMS0rDMQ89uIyvDyrknVPP8889x55138s4776Tkq6mp4aabbuLSSy9d8LnlBTkOLj6jlosX9KoCgUAgOBZZGm9aAsExQDSW4J/1XXj9QRobG1HjUVaXOXEswnS2mZAlidJcG/lOC+1DYfbvb6K4uARd1/H4w5y4qgSrRXQd800oEsfrD5PQE5gcASR56rS2ycjmOK61bzO4+3T8UYmWLp0f3f8w1779J9paW1LOXbNmDf/xH//B5z73ORRlad2DAoFAIBAcbcSbyxwYHh5G0zRkWaagoGCxiyOYJUtBN03Teaepl5HRIPv27UVX46wuyzjiyGzzidUsU1vioG8kSk9/H6OBUVauWMnrkRgn15Ulp0zNJ0tBu8UiFI2jahqgIyvqIc8fx2SNkLfiLfpeyGSgZRf9kdTh/+OPP56bbrqJT33qU/M2hfhY1s3ICN2MidDNmAjdFh7h9MyBnp6eZHhBcYMah6Wg2562AYZ9IZqbm9HUOGtKnfMWne1oIr036pNlN9E8EKShoZ6amhr+Wa9xcl3pUdsIczqWgnaLhSSN/ZuJhKrR0TcCQFVJDlJUx7fVx8jWNrRQ6sjQaaefyS03f4/zzjtv3qcoHsu6GRmhmzERuhkTodvCI5wegWCe6egfoXPQR0dHB8FgkNWlGYZweCbitJlYV+akeSBEY2MTK1euYNs+neNXFlPmmt3eLUZB13USqoZJkRd1/VKO047NYkEOKsTCGej6DE5QQMPzJzejb/nRY6mxaUxFKynacBE33fJVzj+jdv4LLhAIBALBEkQ4PXOgoqIiORQpMA6LqdtoKEp9+yD9/f0MDw+xotCB02bMx85skqkrzaB1YGzEqqqqiu26TiSWYEVZ3rxcc6G0i8QSdPSP0Ds8SigaR9d1FFkmO8NKfraD6uKcBV/HlJ1hZXlpDoO+IcJxC4mIA7M9BIyN8ABEBqPwchD2RfFPHNiRIfO4TJSa4wmFjkO3lPDitmbOOq6KTMf8R2YTfaUxEboZE6GbMRG6LTzGfPtaJHJzcxe7CILDYLF003WdXa0DhMJhurq7Kc6xkp9pWZSyHC1kSWJlkYOO4TDt7e3E43EAVE1n1bL8o369+dZO13X2HRimvc9LPJHA7fYQDAZIqCpWq5UMh4PB7Bzaer1Ul+RQU56/YHsWOe0WVpTmsWO/DVSJqC8/6fR07BiG7WFoiadmUoA1ViovKsacZyYRdRN6WyOSCNHc7WEkEFkQp0f0lcZE6GZMhG7GROi28AinRyCYJzr6R/COjjkHVkWiPG/+F/4vBJIkUe1yYDHJdHd3o7436mBSZJaXGqcTjydUtu/vY8AboKenh4GBATRNw26RMckyHv8I/QkNxWSipLiYWCLBoDfIqWvKsS3AqI/VYqJ2WT6KbMIkmYmM5CB5GvG+5oX2SOrJFgnWW+F4GzhkzHljoadN1igme5B4OIMD/SMMjYTSblYqEAgEAsH7HeH0CATzQDgap7FzmMHBIQKjo9SVOhd949GjTVmuDUWS6OzrRTGNRaEzKTIVRUv/pVrTdLbt62HIG6ClpZnR0VGKsy0UZVuxmA6O5MQS2lj0up4ePB4PNatW8ffdBzh1dTlZGfM/YrJxRTEWE+j7G/FteYORUW9KuuyU0TZYYb2VZRU5KGmmSVizPYRDOSRUlZ0t/ZywqmTeyy0QCAQCwVJDOD1zQFUPho0V+1oYh8XQranLTTgSpaurE1eWZclsPnq0Kc6xktB0uru6UBSF3ZKESZEpLcg8KvbnS7t9B4Zw+0I0NTURCQepLclIq5HFJFNZYMeVZaG5P8jehgZqa2vZtq+bD26onNcRH6/Xy/P/8yjdz99PJOBLSTO7zOR8KAf7xgw6h/0AKLKcduqdLdtDoG8ZCS3Brtb+eSvvRERfaUyEbsZE6GZMhG4Lz/vzTWyeqK+vT4YX3Lhx42IXRzBLFlq3YDhG95Cf3t5e0DWW5Tnn/ZqLSXmeDU3TOdDRgSIr7ACsZoX8bMcR254P7YZGgrT1eenu7iIUCrKmzEmGdeYfHIdFYU2pk/39IZr272ftmrW829TL6WuXIctHdwSvo6OD++67j0cffZRgMJiSJhcU47pAwbnWhiRLyYAGM2HNHAtpHVMjHBjwoaoayjyvSxJ9pTERuhkToZsxEbotPPP6y7djxw4+8YlPUFpaisPhoK6ujs2bNxMKhebzsgLBotLS4yEWizE0NExxjhWT8v6a1paOivdGQ9rb2/CO+HinqZdwND7t+fp7Ud/UWby0H010XWdvxxD+0VH6+vowyRL13aO8ts/DP/Z76fZEUDU9bV6zSWZVsQNJS9DS0ozbH6K113PUyrZ9+3a+8IUvsHLlSu6///6kwyPLMmWrTyXvQ1djOuMSVOdxSO85WiZFZmV5HivL86YNsCApibG6o6Pp+qKG4RYIBAKBYLGYt5GevXv3csYZZ1BbW8t9991HQUEBr7/+Ops3b+bdd9/lj3/843xdet7IzMwkkUhgMokBMiOxkLqFo3G6hvz09fUhoVGUNf/rPpYKVQV2onGdltYWbLa1vN3Yy5nrlqEoMr5AhK4hP/5glHA0TjiWQNfHnAuzSSE7w0pupp1lriwy7Acj3B1t7Qa9QfyhKH/f3sg/9w4Rjo85XZquISEhSRI2s8wHVuXyobrcKeHFzSaZlUUO9vUG6e8fwKQoLCvMPuxpbpqm8ac//Ykf//jHbNmyJSXNbrdzxRVXcO113+CdzjA3P/4yanAYf281ttxhbDnu2V1EH3NyJElCkaSjPjKVDtFXGhOhmzERuhkTodvCM28t/d///d9EIhGefvppVqxYAcA555xDX18fjzzyCF6v13Dh+pYvX77YRRAcBgupW2uvl1g8zuDgEMXZx8YozzjSe+GsG3oCNDc3I9XW8dJbLcgSuP1hZHTi0RDRWIxYNEYsFkVRlLHQ0BkZODMzaenxUJqfyapl+TjtlqOuXVuflxe27uX5bV1gihPUAkTVSLL8ZsmMPWHnf+sTvN7k4cKNLj5Ym5syOuK0mXBlWujt66XAVUBT5zAbVxbPqRyBQIBf/vKX3H///bS0tKSkuVwuvv71r3PNNdckd+k2O72cf8oq/viPOPF4jOF9J1C4fhsWp/+Q10pExxxvRTItSPAFEH2lURG6GROhmzERui088+b0mM1jIVOzs1MjOeXk5CDLMhaLsfcrEQgmo2k63UN+hgYHQdcozj52RnnGMSkSywvtPPPWAL96vZNATAddB11DU1XyM80sy7OxotBBZYGdmK7j92n0JjQkWcZV4CISLaFn2E+5K4sNy4uO2vqTeELlmb/v46W3WgkxSiQewJLlJSe/H9kSRYtbiPpz8XmKGE2MkqVm8Yd3NFoGQlx6RilW88FylOVZcQdG6e3pwWI2U1Oej8NmPmQZOjs7efDBB/n5z3+Oz5canKCmpobrr7+eyy+/HLvdnpK2vDSXy8/fSNegj3caNUZUjaGGkyja+AYmW3jGa0Z8+YCEzWRjdYVr9g0mEAgEAsH7CEkfn2NylOno6OD444/n3HPP5a677sLlcvHaa69x2WWXcfnll/PAAw8kz9U0jdHR0ZT8nZ2dVFZWkpWVlTwWjUZpbGwExjZ1qqioSMnT3NycXC80eVHY8PAwPT09wNguuBNHmVRVpb6+Hhgbbpzsfbe3t+P3j31RXbt2bcpQ5MjICAcOHACgtLQUlyv1pWL37t3ouo7dbmfVqlUpaV1dXXg8Y2sCamtrsdkO7uMSCARobW0FoLCwkJKS1DCze/fuTS6AW7NmTUpaX18fg4ODAKxYsQKn8+BC+kgkQlNTEwB5eXksW7YsJe/+/fsJh8NIksSGDRtS0oaGhsYW5wOVlZXk5OQk0xKJBA0NDQBkZWVRXV2dkretrS2p8bp161IilXi9Xjo7OwEoKytLft0eZ9euXQA4HA5qampS0jo7O/F6x8L41tXVYbUedDT8fj/t7e0AFBUVUVyc+jW+oaGBRCKB1Wqlrq4uJa23t5ehoSEAVq5cSUZGRjItFArR3NwMQH5+PuXl5QD0uUd5p6mXl195BYsWpiLPQmVlZYrdkZGRZHkLCwtT7Mbjcbq7u5N1LSoqSsnb19dHJDI2KlFZWZmyi7Pf78ftdifLNPG50TQteY/abLYp99LAwEDyuSkvL09+sAAIBoPJeyk3NzdFc4ADBw6gaRpms5mysjJe2+fhpd3DuANxArEgCSIga5gUGbNiwqHYsCk2JF2iIkvnnBoby4pycGbl4g7E6PfFUPWxZ7Igv4D8bAefu+ADWCdMH+vv72dgYACA6urqWfcRb+/r4fObf8dQYIgwfvKqW8gsb2V8EEdVVRKJBGrURnhgNaGBSmyKnXxzHlX5di5YqWMxSdjtdoqLi+n1RugdiXPccceRaYrhyhgzlK6PeO655/jNb37DK6+8khKxB+DUU0/l0ksv5SMf+ciU+3BiH7FiZQ3/3NvHD554nX0H+vCpQ2D1kVOzDVtmaMoUiWgsiq5KDO05B1PMRYmznF//xyc5bc0y0Ue8x0L3EeM0NTURiURQFIV169alpA0ODtLX1wdAVVVVyofDWCzGvn37gLEPilVVVSl5W1tbCQQCAKxfvz6lj3C73cn+pby8nPz8g5sJa5rGnj17AHA6ncnZGeN0dHQknfTVq1enfLTs6XCOAAAgAElEQVT0+Xx0dHQAUFJSQmFhYUre+vp6VFXFZrNRW1ubktbd3Z3st2pqanA4DgY/CQaDyVFQl8tFaWlpSt7Gxkai0Sgmk4m1a9empB1uHwHiPWIc0UeMIfqIMZZiHxEIBKb8nmZmZqbUaTLzNtJTVVXFG2+8wSc/+cmUxrnuuuu47777Dpk/kTg4538cXdeTO8AnEom0ecbTJ6NpWjJN06Yunp6t3cllmmh3cuOP29V1PeVFchxVVY/I7nR1nWh3cl0ntmE6u+N1TbfYebZ2l4o2h6prPB4nkUikfUBm0mY6u12DfgLBIOFQmLxMLW15Ne3g8XTfG8bT0rXD+Et5OnRdJxaP4w7qDERD2EckdF3HYpJxWCTcozEybVLa+3BimdLZnalMiUQCTdNQdYlfvN7DW60+wlqQoDZKQokjmYOYbAEki44az8ITzIQ42GQb4eEMOjxxzl6t8PFT8yjNtVGUbWXQH2NH4wFGvF7U6uX8Y08np64px/neWp/ZajO5Tg8/9w7hWIQwoziK2sha1jolr67ryJYwOcv34MgfwrN/I4OxBPqwi2dCGp9Ya0125gWZFnq8UTweDz5JI9tsR5KkZJni8ThPP/0099xzD++++27KtaxWK5deeinf+MY3kn3EdJqP10eRJc5ct4yvf+o07v7v12nvU/FHdNwNZ5FZ3kzOsk5k5eD9qGvgO7AONZJBvj2PleX5nFxbNsWu6CMWro+YaDcej6dNm8nueN5D2U3HbNswXf6JZZrMoeoai8XQNC1tSN6j0Ybp2uhw+4jxY+I9QvQR6cok+oil10fMlXlzejo6Orj44ospKiriqaeewuVysW3bNm6//XYCgQCPPfbYzAUzmaY8MJJ08KUt3cIvk8mUtlOAsQhI42npbs7Z2FVVlba2NiwWS/ILxES76QQzm83oup7WrqIoybyT6zobuxP/Tmd3cl0ntmE6u+N1TddZzdbuYmgzXoZ0ZVJVFa/XSywWS/lyNF7PQ7XhTPfheBtGYwkGR4IMDw1jNStkO5S07SvLcrIe6dp4PC1dOyiKktIGoZjKgeEwHUNh9vf66BiMEFN1TKYEijKSPE/XdWKxGHazxKoiOFUbpa4kIzlda2KZJiNJ0oxlMplM+MMJntkZpGdUx696iOphTFm9ZBbsR7f1jwUHsNuxmBVMuoOwpxBfZw2RaIQMPYNXmhTi0gCfOaUIRZYoybESLLLRPBihra0Nk9lEV08vnz3vVBw286y1mVgnfzDKW/t6CKqjSKYomcv2Mbn7kyQpxZ49bwjX+m0M1Z/KcHyYuC+bv7Uk+MyJY+1gMclk200MDQ1RUJBPIKaT57QwMjLC448/zk9+8pPkV7NxCgoKuPbaa7n66quTX7vGv+LOpo/IsFn40IYKItHTuf+pf9LRKxFSRxntqiXUtxJ73iBmRwBNkwgOFxAPZuOUcsiwZPCtz5yanCo4332Eqqr09/fj8/mSz9xS7iOmq+vR7CMm21VVNW3aTHbH885k90jaUFVVIpEI7e3tKX3lxDJN5lB1tVgsqKo6L22oadqcf1uX4n14pO8Rsiyj6zo9PT2sXLlyTnYn/p1sV7xHzG8fMa7b+MjLZLtLsY+Y+He6Mk1mPvuIuTJv09s+//nPs2XLFtra2lKG9H7xi19wxRVX8Oqrr/LhD38YSD+97VBDVIvBrl27REx1A7IQunX0j7CrpZ8dO3dQ6FRYlm8/dKbDxBuM89d6N2+1jqDpoOoqMS1GVIsS1WIk9Pe+iqAjIaNIMrKkYJOt2GQ7FtmMIkusKHRwfFUmJy/PRj7MMMZxVePHfz5A88AoPtVNQgphr3wbR24fsgSarhNLaCiKCbPJhM1iQlFktISCr3MVgb5KHHIGeeY8Tq/J4TOnFCfLEktovLajhUhcp2bV/8/enUdJlt2Fnf++LfY9cqlcqjKz9r26W+qmJQFSj5YDWKJxy8KSDbaOLYFBYFpzGGGdwSNknwMNx2eGPzzMWGLGNjBiE0YeZmiP0S7kbmipu6u6qrr2NfctMmOPeMudP6IyqyIzqiq3iMxX/fuc0yelfPnuu+/9Im7FL+52kHe8/THedXz3hhq6//TtN/mVL/wVo4XrBHov03Pg4prPrRWSzJx9ijAJsoEsH3tHH0/ubQwnmC/aXJkqceqxxzCr8/yXr/whv//7v79qWf6TJ0/y6U9/mo997GNNQyc2qlCu8dK52/zpt87zV69cplqvUvVK1KnhKgcNDUOziJtJ4uEEn/qJp3j+7z296euulbSV/iRx8yeJmz9J3DZnI7lD23p6Xn/9dY4ePdqU8AA8+eSTQGMM31LSI4TfTedKFIsFXMchE2tPwpMr2Xz13Bx/c2UB23MpOAUqbgVHNbrrjWCVQCpHOFoAzQMNlGvg2QGcWpj8YpZF28DQTMJGiNJYhYsTRb5zIcdzT/ayt2f9m4n++femuTpVaiQ85gKxvf+NUDS/PE9G1zRMXcdxHQxdp2a7hHUN3XRJ732TQHyB+UunwIaXLje+ufnIU40x0wFTZyRjcnGqxtjoKPMHD3Lp9hyH9nQ9oEatvXp5gppbw8UllJ1Y17nB+CKZ/W8wd/FxQk6IP3tlipHuMF3xANGAxpunX+HL/8f/woWzrzWdp2kaH/zgB/n0pz/Ne97zni3dHyceCfLeJ/Yy2J3k6SODfO3V67x2aYxyrTEMptFDZzDYneSTH3wb//B9J7bs2kIIIYQftS3p6e/v5+zZsxSLxaYJcC+99BLAqklbfnDs2LHlDxTCP9odN89TzC6WWVzMYxk60eDq7tvNKNdc/vL0DC/fk+wU3SLoNtFd4wQT8wQSOcxg9YHlKE+nupihOt9DZb6HYi1MQA9Qn0/zb/+qxhPDCT70eDfJyMNXIQN4/Waeb5yfo+Au4FAhuvelpoRniaGDpzRsx0bTdeqOR9BqPKNo9wQaMHfpFJqj8dJljZGuMG+/05MyMjxEV6/NhYkKY2Nj6LpOdypKJrG+xPLK2Dy2VwcUgejDl3leKdI9SXVhlNy0RtAO8uXvXiVbOMuLL77I7Oxs09/GYjE+/vGP88//+T9fNWF2KxmGztHhbvYPZHjPY8OMzea5cGuO2cUSoYDFod1Znj46SDa5/mR2s6St9CeJmz9J3PxJ4tZ5bUt6nn/+eX7iJ36C97///Xz605+mq6uLl19+md/4jd/g6NGj/OiP/mi7Lt02soGUP7U7bgvFKq7nsbi4QCKytdeaXKzxf35zlOlCjbyTX0524oM3ifVfx7BaTxxsRdM9wulZwulZUnvPU8tnWLh2hOlSnagZ5ZXrLmdHi/zoqS5+eMXeNCuV6y5/8N1xKm6ZiioRHjxDOLq4KuGBO+N5Dag5Hq7joGlgGfryJpmR7gmUpzN/+SRBPciXX5lipCdMNhbAMAxSMYM9XTA2MUEymeLMtSnefWpoXf9QTM0XcZWDblXRDQ948NBZz1NcG2+s5rO3P42ua6T2nqd0DcZf+zo3Ry+gvOYJsQO7h/nUL/wCn/pnn2xaLardApbBvoEM+wYy/PCp4Y5d90GkrfQniZs/Sdz8SeLWeW174j/+4z/O1772NV544QV+6Zd+icXFRXbv3s3P/uzP8tnPflb26RGPjNnFMo7jUqlU6O3euqFt50aL/P53xynWq8zW5/D06oaSnVY0DULJeXof+y6lyd0s3jpEuVYm6Sb5z9/3yJVsnn2i576Jxf93ZoZ8xabgLWAmx4h0X2+Z8Ny9noapaziui24Y1ByHcOBuj1K0d4xaPtPoSdGDfPlvp/iZZwaXr9+XCpIrOdy+fYt4PMbkfJG+bHzN9+t4CqU8NH31yjEPoxxF4VyRhe8uULvVPBdI0zROPPYEx3/gvXzkH/xjHj/Q39GERwghhBBr09Y085lnnuGZZ55p5yWE2HbzhQrFYgGlFInQ5t9SSim+fn6e//f1GSpuhTl7DjOySM+RVx+6EeV6aRrE+m4T7ppk8eZBFib34CiHb72pqNY9fvLpXasWOSjVHL5+fp6yV8TDIT7wBmvZP9TQNVyvsQS2rlk4bmP/niWpkfNUF7rI2TkuTpicuV3k1J74nXpqDGaCXJwosriY5/JoaF1JT6vlN1v/XWNdF08pKHpwtsrN84t4xeZkSbOCJPf+AP/9P/0II3v6uThRwnEcyrXNJaNCCCGEaA/pW1uHhYUFPM9D1/VVmzSKnavdccuXahRLJSxDX14GeqNcT/GHL03w6o08i84ieTtPuGuCzIE3mvZg2WqGZZPZf45AfJHcleN4yuNvrjaGpP3Dd/ZjGncTnxdPz1KzXSpekUDXDQKh8gNKvkvTNEwDbNfF9Qzqtouh310mWjddUnvPM/fmE1TdKl89O8ve9N1zk7EYkaDB5OQkyWSCXKFCOr62njVD1+/soWPwoOUqr43Nw20H3qjCNRsU3JsuBXYFCB0foRp4hlRsD5cWgxw0GzG3bZua3b4Y+Ym0lf4kcfMniZs/Sdw6T5Kedbh58+by8oLyAvWPdsatVneo2Q6VSoVwYHMJj1KKP3tliu9fX2TenqfslkkOXSI+ePWBQ8e2Uqx3FN1wmLt0Cs9WvH4TarbHx394gICpU3dcXr6yQNkt4Wku0d4r66pbo7dHw3FsdF3Hdj0C5t2FH8KZKaxYnnwlyFguxPcuTTKYaIx9jsVi9CaDXJ9eoFqtcWNyYc1JT39XnMtTJl4thOdqq1o+t+SS/14evrsICyt6hTRgnwWnQux+qgflwfjf6pTcEq/fDPB3HmusJue4LrYjSQ9IW+lXEjd/krj5k8St8yTpEWITCpU6AOVymfQmV237xpvzvHxlgZyTo6yKZI+8TiQ7tRXVXJdI1ySa4TB34QlmbA81rvjy307ysXf08cbtIvmKQ02VseIzWOHVm6o9jGlo1B2vsdPynUUNlnp7NA0Sg1eZu5Cg5tX5m5s6gyfu7muTiVrc0jXm5+eYjkXWvPLN7p4E5nkL0HBrIQjWUEpRvVUl/1Ke4pkiylnRBxTR4FiQgf+um2A6cKd+GprhEs5OUpkNUbWT3Ji5O+RQVuERQgghdiZJetahv7//vjvkip2rnXErlGt4nqJeqxFeY69DK2dHC/w/r82w6CxSckpkDr6xLQnPknB6lu6jrzBz/klydo7vXdcZ6Q5zdrSI4zo42MTS4xsqW9c0DE3DdR0Mw1jd25OdxAyXKNTzTBTTVI0EezIhoNFTlAib5PN56o5LoVwnEX34Zp/DvSkCRgANqOeiLJ6bZvHlReoT9dV/vNuEEyEYscDQGKuU2J9tvkYoPUN5egBXuVyZKtOXCqKhISlPg7SV/iRx8yeJmz9J3DpPkp516O7u3u4qiA1oZ9zypRqVSgWl1IaHt80V6/zhf5ug7FbI23mSQ5eI9mwsodhKwWSO9P43mL/4GEEnyB+/rDANjZpXRtMhmFrfJp/3MgwN9wG9PfGB6+SuRElZKa7m4MSdfXsA4iGT27kirucxu1heU9Lz+IE+vPw03tlvM//iWVg59yaowdEgHA9C+uH/AIWScwBUvRqXJ+8kPZr09CyRttKfJG7+JHHzJ4lb50nSI8QmVOoOtVoNgJC1/m9rHFfxH78zTqFWZ96eI9w1SXzw6lZXc8Oi3RPU8xlyExqOMimUPbRgHTO8gBHY+EpyD+vtiWQnyV09RsWtcOZWoWn57ETERM1VKBaKzC6W2dufvu91SqUSf/qnf8q/+3df4MbLL606HtwTJPl0ksiJKLql4ynFjYkFAIb7UqtWrltiBOqY4RJ1O8b4QmOonBUIENjAa0AIIYQQ7SdJjxCbUKs72I59Z2Wy9X/L/91LOW7PVZi1ZzFCRTL73+jYogVrlRp5k0qui3w+guuaQJ1ocvND7x7U26NbNqHUHJV8iIVynLFcjcE7Q9wiAQPL0CkU8szlUy3n9bz66qt88Ytf5Etf+hL5fH7FhS3CJ+J0vTtKcGBFL9E9axjomra8gWorZriEU3ewXY+K7REMBImGrPv+vRBCCCG2jyQ9QmxCzXYbq69sIOEp11z+69lZSm4JW9n0HjyNbjptqOXmaLpHfPAqM2cyKAUKDy20sOly7+3tMQ0Dx/WwmlZymySX68JTHmduF5aTHoBo0KBcLuO4HjXbJRQwWVxc5Etf+hJf/OIXee2111Zdb/fIfirZxyh0d2MO3CbQ/+am6m+GylQXHJSCst1IkKIh2XRZCCGE2Ikk6VmHM2fOLC8vePLkye2ujlijdsVNKUXdWUp61j+f56vn5ijVHBadRSLdYwTii1tWt61mmA6GWcJ2o4DC0Tef9MCdJaxdD9fzcFytOenJTjN3xSNfzfO3F11+7NTd8c+WqVGq11FK8c1vfZs/+r9+jz/5kz+hUmkecheNRvnoRz/KJz7xCY4cf4wf/qX/wFh+gsKswh66TCDYPLdH1zX2D2bWVnerhqc8XE+B0ejhiYUl6QFpK/1K4uZPEjd/krh1niQ966CUWv5P+Ee74la3XZRSOLa97qFtc8U637mYo+AUUJpDcujSltZtK7m2hXINNM0FzQEUNX0RTxn3nfOyVrquoXlaYwUbXcf1PAy9kUAagRpmuEC9Gma2FMZ2veXk0q4U+dbXvsn/9hu/wu0bq+dAPfnkk3ziE5/gox/9KIlEYvn3P/b0fv7oG2UK9Rz58WG6RjY/f8pTEIvFiAQtIjK8DZC20q8kbv4kcfMniVvnSdKzDuFwGMuyME15bH7SrrjV72xEaTsOoXUmPS+enqXuOhTcArGBG5jB6pbWbSu5tTCeC64TQjNtlFUE3aNS14hucm8iAFPXsF0XT5nYjodxzyp4VnQRp5oFNMbmK+RGL/HVr36Vl156CcdpHgqYTCb5qZ/6KT75yU9y6tSpltf6+Wef5Ct/fZGYmaQwvpdE3y0CIXuDNddo/FuliMdi9KSjGyzn0SNtpT9J3PxJ4uZPErfOkye9DgcPHtzuKogNaFfcPE/d+emhreOz/+h8lVdv5Fl0FtHMGokdtFpbK249iFfxQOloRh1lVlDKo2pDJKBveplmXQONRm+PrmtNCxOEEyVyt+bIj5/mV7/xP5NfmF91/tueeppf+oWf58Mf/jCRSOSB19rdk+TZdx3iT75pUyzlyV0/TO+RNzZUb9cOoqGjGzqJWITedGxD5TyKpK30J4mbP0nc/Eni1nmS9AixQcsd0kqta1vKv76Uw/EcSk6J1N4rO3LxgiVKgedYuDUNUKApMOp4eGhKp2p7hAOb6+3RNA1DVziui2ma2K6H6WoUzxRZePlvqN8usHIL0Xg8wbG3v4uP/NQneP973sWJvb1rvt4v/+Q7efFvrpC2u5if9chPzpLYtf49h+xSFB0D07TY05OkO/XghEsIIYQQ20eSHiE2aGkcbqNnYm3n2K7HmVsFSl4JzXCI9t5uYw03T7kGKA1la42ERwPNqKEApRpD3ELWg3t7PKWYmi82/a43E2uaD6TrGsp1qV4rkz9ToXKujKqvGOesabz9bW/jve99L0dPPsHl6RqDw/uW5wCtVVcqwmc++k5+7T98k7JdYuHaMYKJRYKR8prL8FyDaiFFRAuSTkQ5ta9XNiYVQgghdjBJeoTYoHvnHq714+6bYyWqtkfZLRPumkI3vIeftI08tzEx36traCg8FJrhgO7ieRqeUrie2tAeRUvcRZfy62XKr1fwFtxVx7V4isjQExw4/sP8T//gCQAWyzZQQ9f1B+6lcz//8P0n+cbrN/j6ay4TpTrTbzzFrpMvY4XXNreqON2Dcg3i4SSn9vUyvCu17joIIYQQonMk6VmH27dvN1aZMgx279693dURa9TuuCnFmrOeV2/kqXt1HM8h1T2+5XXZasoxUR4oV2d5QJ9uo+sunmeggLqrMFuMcPPU0pyn1SvTuDWPyqUa1dcr1K+vHLwGWlAj/licyGMRFnMfIFDro6pHl+f7LBWp6zrGBpIegH/zz97Pc5/L4Y17TJZHmTr7FD3HXiEQqTzwPNvWyI/tI2iECZpB/vEHTmFsYMnyR5m0lf4kcfMniZs/Sdw6T5KedZifn19eU11eoP6xU+JWtV3OjxUpu2V0q04oNbdtdVkrzzVRzlJv1FLyoqEZLsppDO2zHQ9azOtZOaQNT8GYCxcdZq8WocWiaeawReTxGNETMaKxILVaDb1Qw6k6OK6i7iiClracUOmatu7hbUtS8TD//lee5R/86/+EmlVMV2Dy9XeS3n+WaNfkqh6kxr5MioXrR/GqcTKRHo4MdfOex4c3dP1H2U55z4n1kbj5k8TNnyRunSdJjxAbZN75dt8wDFxv9bCslc7cKmC7jaFtkV0TaNrOX5tfKR087uzRc6e+bgA0haZ5KKVju6ppxbVV5hqJDhcdKK2+ZyNtED4VJvJYBDeqgaaBoS33EGmGjbqTcNUcj6Cl493JwzY6vG3JUG+KP/gf/y4ff+E/Y8wYzJQnmb/4OPmxHPHBq4RTs2i6wlOKWjlE8fYR7Fw/6VAPiXCUf/NzH5C5PEIIIYQPSNKzDocOHXrwhzuxI7UrbpZ5J+kxDdyH5zycvlWgpuq4yiXig6FtQGMRA6VAa9ygpjTwLDRA0z2U6wGNxCdg3n2+btEldlGj+kYFZ3L16nRaUCN4NET4RJjgcGA5NspVOJ6HovHTsizMgMK9k9hUbZdE2KTmeFiBxnnhwOaasZG+NF/513+fX/q3/4WXzhmU7CKL5SC5C2lymsIIllCeiWeHMTSDrnAPmUiKz/3jd3Nwd3ZT135USVvpTxI3f5K4+ZPErfMk6VmHUCi03VUQG9CuuFl3JrKYhomzcqWxFZRS3JqrUvOq6FadQHyhLXXackprrFSt2SwNb1NOGABNdxvD31DUHQ/Tg9qFGpUzFWrXaves6X2HDuwx4JBJ9xOppk1Ilxg6OF5j7yPX9QiYFpqmrVoSvGp7hO/ENRYObPo204kw//GzP8GffftNfucrr3B7Okbdq1NzKzjKRtcNzJBFIhgnE4/wws+8jx8+NbTp6z6qpK30J4mbP0nc/Eni1nmS9AixQUsT6A1Dp9Zisv698hWHUs2l7tkE4vk1L3G93ZTSUKox4kzX63iYYN9NevAU3u06pQs2xSv11ctMA2a/hbNPg4MWhBs3rlmtH8BSguN5Hp5qDJtTnrH8TVjgTu9ate4STYUaPT1Ba0vuVdM0/t67j/LcDx3hv37vKl9/7Tpnrk4xu1gmFg6wKxPj/W/by9/9oSNkEuEtuaYQQgghOkOSHiE2SNM0LNPAME2chyQ94ws1AGzPJhLLd6J6W0S702Oj0I0KmpvAq0fwbmuoNx14s4BXbjFPJ2kQPhkmfDKM2bW+ZkbXGz09KHA9hXKN5Z6egKnjKUXF9uiJRImHA5ua09P6+ho/8tR+fuSp/VtarhBCCCG2jyQ961AsFvE8D13XicVi210dsUbtjFvANLBMC8d98H47Y/M1POXhKgcr6qek5y6tfAvvRhEmr+BWWi8zHToaInwqTGBPYMPjlHVNw73T0+M4Lp5rsLQ2XNDUKddclFJEohGSMRkesBNJW+lPEjd/krj5k8St8yTpWYerV68uLy946tSp7a6OWKN2xi0SsggGg7iewnY9rPvs1zKWq1JXjTWaA9HCltahndzFEuXXFqhcmMbLt9i/xgBGLIzDQdLHI1jBFhv2rNNSx43nedRcF8fW0F2FrjWGFOYrDoZhEAlHSEaDm76e2HrSVvqTxM2fJG7+JHHrPEl6hNiESLCR9ADU7PsnPeO5GrZXR9M9zHCpk1VcNyfvUDxdpPB6gdrt2uo/0DTYlcJ4Io+3LwBGAF0z8YytGWamaRq6pqE8DwW4tQg6OvFQo7nKlRwSySS6rtGblm/HhBBCCPFwkvSsQ09Pz/LuucI/2hm3pZ4eaOwh0+ojuO14zBTq2MrGihS2dX8ez1NcG88BsLc/vTwfxi26FM8WKZ4pUrlaWb3yGmB2h/CyT6H6RyBTQD/wF+AqXLvx595D5jWth6aBpzx0FUW5AQJmgN5kgLrjUao59A6kSUSCREJbs4iB2FrSVvqTxM2fJG7+JHHrPEl61qGvr2+7qyA2oJ1xi4YszDuLGdTs1vN6SvXGHjeucjFCLYaIbbH7JTYruUWXwvkSxTfuJDotqm/tChHc34eeTBFMFynMD2F7EbxKEOWEQF+a29PYwHOrLM3rUbUkGhAyQ/QmgyyUbTRNI5VKsSsjvTw7lbSV/iRx8yeJmz9J3DpPkh4hNiFyZ7nkYDBIzbFb/k213sgmPOVhGas36uyEpV4Yu+DA2SpcrnNzbL51opO1iD0WI/5YHD0Vp7bQRW28hvKqBEITOMWDYGio/B609GVgqadn6+q7tAaCXY4BGqZmsisZZL7oEI/HMU1Dkh4hhBBCrJkkPUJsQvTOxpjhcJhyocX8F6BiN3p6PDy0NiY9S4nNvT0unlK4BZeb352Gy3UYdVoPXcuYxE7GiJ2MERwILq+8ptxGIqcFdVQ1RCA0TqV4CBSoxaHlpAfVstgNW+qbcsoJdBr79KSjJoWqw1BvlnDQkpXbhBBCCLFmkvQIsQmmoRMLB4hFo8zPzeEphb5iqealYW9KKXSzfUnP0pA2ACoeXK1z489v3TfRIaHDgQAcCDD0eHfLJaY1w0MzHfSgjlMOEAhMoxsVdC+IV+xHuXfn1GzlbjlLm5Ta+V5CBNC1Ru+PaZp0dXUx1JvcwqsJIYQQ4lEnSc86nD9/fnl5waNHj253dcQatTtuyWiISCSKUopK3SO6Ytnmpfn9CqCdixgUG4kOV+swdp8enbSJs9dsJDonsxh6Y7W5B+2pYwSquKEooKG8IIHQOG55LygDtTgM0dGtzXju8KopvHoIQ5lkgg75isvA4CABy2B4V2rrLyi2jLSV/iRx8yeJmz9J3Dqv7UnPX//1X/Prv/7rvPTSS1SrVQYHB/lH/+gf8S//5b9s96W3nG3b2MjmcHIAACAASURBVHbreRti52p33FKxEJFoBE3TKNfcVUnP3dFmCm1LB4FBfaZO6VyJ4tki3Go9vM7MmERPxIifimH1Bbg+sQCAoev3XeTgXkaghm7G0AzwvBDB8G2qpX1onoaaPQGR0cYcnC1OfJzFflBgKJNkUKEbBr09PQzvSmGZstrNTiZtpT9J3PxJ4uZPErfOa2vS86UvfYmf/umf5id/8if5vd/7PWKxGFevXmV8fLydl20by7Kafgp/aHfcUrEQhq4TDocp1hy6CTQdV1uY6CilqE/UKZ4tUjpboj5Zb/2Hd4auDbwjS2h3aLknZyPLShtWI5nSwzpeKUIgNIYZmEXZWZxaEoq7ITG+pTmPUmDn+zE8C9CIWBq9PT1YpsnevvQWXkm0g7SV/iRx8yeJmz9J3DqvbUnP2NgYP/MzP8PP/uzP8ju/8zvLv3/mmWfadcm2k+5Hf2p33BLRxj490WiUUn5+1fGg2RhCpqPjuet/yylPUb1VpXS20aPjzLeeFxToCxA9FiVyLMqYVwJNI9gfahq6pusa+wcz67q+piuMYBUvFsQtenhuhEjsIvn5d6F5OmruGCo+/sAhcuvllDK4lSRhQiQiJj3dXfTu2sXuniTBgIzK3emkrfQniZs/Sdz8SeLWeW379PC7v/u7lEolfuVXfqVdlxBiRzANnUQkSCweZ2ZmBtv1sAx9+Xgq2vgWx9AN3Fp4XWXnv59n7i/ncAtuy+OhoRDR41Fix2NY2bvfFu1na1c2s8JF3FoILajh2gms4CSGtYBbT6OqGVRxN1poYsuuV5k8hImJ7ll0RSDb20c0FOTwnq4tu4YQQggh3jralvR8+9vfJpPJcOHCBZ599lnOnj1LJpPhueee47d+67dIJBIPPP/cuXMMDQ01/V2tVuPChQsApNNp9uzZ03TO5cuXKZfLAJw6darp2OzsLGNjYwDs2bOHdPruEBnXdTl79iwA8XicvXv3Np17/fp18vk8AMeOHcM07z62hYUFbt68CUB/fz/d3d1N5545cwalFOFwmIMHDzYdu337NvPzjZ6BQ4cOEQrd/aBaLBa5evUq0Ni1d+UmVg+aADcxMcH09DQA+/btIxa7u59JtVrl4sWLAGQyGXbv3t107qVLl6hUKmiaxsmTJ5uOzczMLA9NHBoaIpW6O5nccRzOnTsHQCKRYGRkpOnca9euUSgUADh+/HjTDsS5XI5bt24BMDAwQFdX8wfb06dPAxCJRDhw4EDTsVu3bpHLNVYtO3z4MMFgcPlYPp/n+vXrAPT29rJr166mc8+dO4fjOASDQQ4fPtx0bHx8nJmZGQD2799PNBpdPlYul7l8ubFUczabZXBwkO5UlNmFxopiF6/dJmp66LreeE6RxuvFwMCuBKnVGsPFTNNseg5KKer1xnA1XdexLAsjbDQnPDoER4LET8SJHYthJhtlu667pnI1XSNgNQ+/s20b784mO4FAoKnHxnVdHMdBqRqeFsdMmNgzQZQXIhK7QH36B0EDNfkEeuavALfp3KVyTdNsKtfzPFzXXb7Xe+trl1LUFnYRdgPgeQx2xQiEYpzc10vAMpicnGRqagqAkZERaSOQNsIPbcS9Ll68SLVaxTAMjh8/3nRsenqaiYnGFwjDw8Mkk3dXKqzX67z55psAJJNJhoeHm869evUqxWIRgBMnTqDrd798mZubY3R0FIDBwUGy2ezyMc/zeOONNwCIxWLs27evqdwbN26wuLgIwJEjRwgE7rYhi4uL3LhxA2hsttjT09N07tmzZ3Fdl1AoxKFDh5qOjY6OMjc3B8CBAweIRCLLx0qlEleuXAGgu7ub/v7+pnMvXLhArVbDNE2OHTvWdEzaiAZpI+6SNqLhUWojlt6n69HW4W3lcpmPfOQjfPazn+W3f/u3eeWVV/jc5z7H2bNn+c53vvPA4TCND1rN8w+UUsuTvhxn9RAfx3HuOynM87zlY16LXRTXWu7KOt1b7tKHuJXlKqVajtl0XXdT5d7vXu8td+W93vsMW5W7dK+tYrPWcndKbB52r7Zt4zhO05t+yYNi06rc7lSEqwGLcDjM4swcwYi3XK5l6MRCBou2SbUeXlXeyrLh7jyg8IEwRtQgNBwieChI6GAIPaITDAZXxWgt5WpqdVwVak3nWpE8rurGCbjY9TRWcBxN5dGqWZThURt/nODI95Y3FlXqbrlKqTXVVymN0ugpdKWjuwG6QzUy2S4S0eDyZqRrjc1OeR1KG7G63J0Sm062ESvLtW275bEHlbt07sPKbWWtz7DV+ffWaaWH3Wu9XsfzvKYPqK3K3egzbPWMpI1Ye7nSRkgbscSPbcR6tS3p8TyParXK5z73Of7Fv/gXALznPe8hEAjw/PPP87WvfY33ve9996/Yim+GobGs7tKb/t5vSe49534Twpa+OV/63yutpVzXdZmYmMCyrOVvTO4tt1XALMtCKdWyXMMwls9dea9rKffen/crd+W93vsMW5W7dK+tGqu1lrsdsVmqQ6s6ua5LsVhkYmKi6Zuupft82DN80Otw6Rlm4mF0TSOZTDI1MYZpmk33ko5YTBYN3HoIlI6mt36zLl1Lu7MsgG7pDP/qMJqhUbfrqAcsRPCgLxGWj7X4Ew1tTefqwTKqZmNlLOpTCtdJo9Um0cwsei1MPbebanyOcPf15fOW76fVHkAtflceP4pTzBJyowR0GOmJUalUSAQUjuthmcaaY7NTXodvxTbCdV3m5+ep1WrL77mdGJuH3etWthEry3Vdt+WxB5W7dO6Dyt3MM1z6gLGyrby3Tis97F4DgQCu67blGXqet+73zU58HW62jViqy8zMTFPP1U5uIx5W7k6JTTvbiKV6ViqVluXuxDbi3p/3q9NK7Wwj1ktTG0mV1uAd73gHL7/8Mq+++iqPP/748u8vXbrEoUOH+M3f/E0+85nPAI0EaanLckk8Hm/50LfT6dOnl7uCV3Z7i52rU3F7+fwol2+Oc+niRU7sjhMO3H1z//tvj/K3N2aZrc/Q9/ZvYoZWN3J+4DkmlflenIKLPetRuN1D2MriBnsxIzWqWoXYnlcJdd1cd9n1xV7yV95FSEWw3Ag/cjxNpVojmwxz4sgBPvHh9xIJySo3fiBtpT9J3PxJ4uZPErfN2Uju0LasYuU4ziVLOdZOS2iE2KzuZIR4PI6m6yyWm7vQ01ELU2skQc46FzPYSXTTIRBbwIwZKCOM0iMEqTMQqRMlSkiFKd58G9XZ4XWVW1/sJX/9KUwVwHQjPDEcY+9Ahl0JnaVtjxx3dXe7EEIIIcRatG1424c//GG+8IUv8OKLLzb19PzlX/4lAE8//XS7Lt02+/btw/M8Sdh8plNx683EOH9zhmQiwXypyK7U3cmQvYkgptYYslnPpwklVy9t7RdWpNQYphfajW5aeFqYI1mPiq44N9OYd1O8+QR2oYvo4BvoVutNU6GxH091ej+lsRMYXpCgG2dPNsQPHOxhqCtMOtxLrgK7+vqwndYr2ImdR9pKf5K4+ZPEzZ8kbp3XtqTnAx/4AB/60If4V//qX+F5Hk8//TTf+973+PznP88HP/hBfvAHf7Bdl26be1cvEf7RqbjFwgHikSCZTJZr1xaoOx6BO3v0HOyLoGkaIT1ENddNYvfVjtSpXYKJHAvOIcx4D3rNwdYDHM4qNDzOzsQwMSnND1Ff7CO86xKB5ARGKH93kQNPpza/m8rMPpxyioAXJqSi7O2N8d4T3Qx3R+hNBnE9RcF2CYdC2NLT4xvSVvqTxM2fJG7+JHHrvLbu8vfHf/zHfP7zn+cLX/gCn//85+nv7+fTn/40n/vc59p5WSG2TX82Ti6fQtN15ov2cm9PNhagK25RzIXIFVJ4jolutt5k1A+UArscI2wFiYYz9HcbTBcK7IoqgobHGzNBAm6AklumPHaM8tgxNKuKESijPBO3FkF5JqYKEPbCBPUQb9uX4ukDaQ70RkmE7zZNSyvZtWn6oRBCCCHeAtqa9ITDYV544QVeeOGFdl5GiB2jvyvOxduzpJJJZov5piFuR/pjTOYrYGtUF7NEslPbWNPNqc73gmeQDIQ5NhCnvy9BOZlkbm6OiFvhB/o9ri1o3FqMEdWi2NjY9TBePQloGMrA9AKYukVPMsjb96V5YjjJUFcY01ixQgv3XwFOCCGEEGIt2pr0PGqq1eryfiP3bgAmdrZOxi0WDpCMhshmu7iSy1Gpu8uruB3qi/KdizlM3aSa6/J10lOa6SegB7AMi/cey5KNBRjPGUQiYcrlCgsLCxw0K/RGXOYqGnNVi1wlgKvA0DViIZO+TIQTuxPsyYYZSAfJxgOrrtPYA8GlXrdbrbYtdihpK/1J4uZPEjd/krh1niQ963Dx4kVZXtCHOh23we4EuUIFwzSZKdTZk22s1ravJ4KhN+b1VBa6UQr82Hnh2RbVhS5SRoRE2GRfbwRd08jELHIlm/GcSSTSuGfnno3FTMNY3n9L0zQyUYvuRKBpKNtKk5NTzJYVY2OjaKdG7vt3YmeRttKfJG7+JHHzJ4lb50nSI8QWG+iK8+bNGbq7upiZnmIgHcLQNYKWzt6eMMWxMMVqmHohRTCxsN3VXbfy3C7wdCKBCI8PJ9DvydzSUYt01KJmexRrDlXbo+54KAUBUydo6gQtnXBAxzIevmLNvbN4/JggCiGEEGJnkKRnHTKZzH13yBU7V6fjFgyY9HfFqVR7mZqaYr5o051oDN16YjjBpYkSpm5SGNtLMPFqR+q0lcoz/QSNEIZm8LbhRMu/CVo6QWv1cLX1CkcixHSNWDwuc3p8RNpKf5K4+ZPEzZ8kbp0nSc867N69e7urIDZgO+I20pdmdCZPMplkarHQlPS8eHqWkhsnN9+LXY5iRUodr99GVRey1BYzZANRuuMBBtLBh5+0CYlkCiseoLuri4Ap/zD4hbSV/iRx8yeJmz9J3DpPdkQSog1SsRCpWIie3l7KdZdCpbE8tWXovPtwmqgRxcCgMLZ3m2u6dkrBwo3DBPQAESPC+49n2977YjsKy7IACFqS9AghhBBiYyTpEaJNRvrSpJJJgqEQU/n68u/feSBNJGAQM2OUZvpxau3tLdkq5Zl+7GKClJViIB3kiZHWQ9u2ku2q5cUPApL0CCGEEGKDJOkRok36s3ECpsGuXbvIlWwqdRdozHd518E0MSOGrkyK4zt/VTLl6izePETYCBPUg3zo8Z6mBQzaxXY9LMsiYBoyp0cIIYQQGyZzetbh0qVLOI6DaZocPHhwu6sj1mi74qbrGnv701TrDhPjE4znauzrjQDwQ4fSfPPNeWJGjMLEENFdt7HCO3duT2FiGLcWIhlMcrgvysG+aEeuOzk9i9IM4pEgsK8j1xSbJ22lP0nc/Eni5k8St86Tnp51qFQqlMtlKpXKdldFrMN2xm2kL00oYNLf389csb7c2xMPm/zgoTQJM4GhAsxfPoFSDylsmzjVMPnRfcTMGAHd4kNP9HTkunXHw7btxnNx7Y5cU2wNaSv9SeLmTxI3f5K4dZ709KzD0qaKMszGX7Yzbqahs28gQ7XuMD4+3tTb8yMnuzh7u0BdZZjOOxTHR4gPXO94HR9EeTpzFx9Hdxu9PE/uS9KX6swcpPKdBDEUDhELWx25ptiYj37hJabyteX/X6vVWNp9N/hXueXf9yaC/NHPvGM7qijWQP6N8yeJmz9J3DpPkp51OHny5HZXQWzAdsdteFeKq2Pz9Pf3c+PGdfrSQSIBg4Cp8/ef7uN//eot4machRuHCMRzO2rD0oXrR7CLKXoCWbriQX68Q708AJW6R39/P0ePHOHxA30du65Yv6l8jeuz9xmeWXA6WxmxYdvdVoqNkbj5k8St82R4mxBtZho6+wcydHV1EQwGGZ2rLh/b1xvhmSMZkmaSgBZk7uLjuPbO6NUojA9RnNhDykwRMYN8/IcGiAQ6t4Jaue4SDocBiIc3v9GpEEIIId66JOkRogOGd6WIhCx2797DQtkmV7o7R+XHHutmb0+EbCCLqkeYOfsUbn17P+RX5ntYuH6EuBknZsb48FO9DGZCna3DnaRH0zRikvQIIYQQYhMk6RGiAwxD5+hQN5lMmkQyya25Kt6dlQsMXeOnf7CfVDhIT6AHt5xm+o2ncWqdTTKWlKb7mbvwOGE9QtJM8t5jWX5gX6qjdXA9RaXuEYlEiAQtDEOaKiGEEEJsnHySWIeZmRkmJyeZmZnZ7qqIddgpcRvoTpBNRBgaGqLuKiYX7k78TkUsPvW+PXRFw/QEelDVJNNnnsauRDpWP6Vg4cYh5i+dIqLHyVpZnhhO8KOnujpWhyWlmotSqvGfXd722AnxVrBT2kqxPhI3f5K4dZ4sZLAO4+Pj2LaNZVl0d3dvd3XEGu2kuB0f6WG+UKG3t5fxyUmysQBBq/HdQ28yyC9+YIj//Wu30ArdzNRh+o2n6T76PQKxfFvr5Tkmc5ceozrfTcpKETfjPL0/xXNv7+3IJqQr5SsOpmlRqVSoFuYZH3e2PXZCPOp2Ulsp1k7i5k8St86Tnh4hOigRDTK8K8VAfz+GZXFjtnl9/kzM4hc+MMTudJSeQA+GE2fq9DtZuH4Yz2nPIgL1YoKp0++knuulO9BNwozz3JO9fOSpXkxje5bSzFccEokEAKmozOcRQgghxOZIT886DA0N4Xkeui65op/stLgd2p1lfLbAyMgIly5eZDpfoydxd++bRNjkU+/bwxe/eRt9RqfgFsiP76U0009q+CKR7jG2ovOlXoyTv32Aylwvlm7RE8iSCDVWaTuwK7r5C2yQ7XoUqw4jfQl6simOHOrfMbET4lG209pKsTYSN3+SuHWeJD3rkEp1djK32Bo7LW6WafDY/l38je3Q3dPDrZkZEmGTkHW3JycSNPj59+7ha+fn+fo5nYgRYdFeZP7SSYqTu4n3XyeUnkU33HVf/95kx9RMMoEEET1CXyrIP333INn49vasLJQcNE0jmUyxd7CXTCazrfUR4q1ip7WVYm0kbv4kces8SXqE2AY96ShDvSlcbw/5fJ5r0xWO9Eebdma2TJ0fOdnFk3sT/N/fn+aNUZOoF2WxGGDuQhp0j1BinlBmmnBmGjNUWXUdpcCpRqjn09QKaer5NHY51pTsJCMW7zuW5Qf2J7F2wCppM4U68USCQMCivyu+3dURa9B7T0/lVvydEEIIsdU0pe6sm7uNPM+jUCg0/S4ej0uXn3ikOa7Ht0/fZGp2njfffJOBdJD+9P2Xqb44UeLPvzfFdL6O4zlUvAoVr0rNq4ICzXQwzDq62dgDSKHh1kJ4dqPnxtItAnqAkB4irIdJhC3edzzD0/tTOyLZAajZHqdv5dm3bx9Dg3088/jIdldJCCGEEDvMRnIH6elZB8dxUEqhaRqmKY/OL3Zq3ExD5/EDu/huzaavv5+x8XGiQYNkxGr594f6ovwPf2eEy5Mlzo0VOTdaZKHs4CmPqlfFUQ6e4+E5HgAaGrqmEwgECeoBdE1HAwYzId42kuAdB3ZOsrNkplDHMAxS6TS7e5I7NnbiwSRu/iRx8yeJmz9J3DpPnvI6nDt3bnl5wVOnTm13dcQa7eS4peNhDg5m8TyPUrHElalFjg3Gmub33MvQNQ73xzjcH+O5tysmFmqcGytyaaJMvuJQqrlU6o15PrquEbJ09mRDjHRHGOkOM5gJLS+RvdMopZgr1slkshi6zmB3YkfHTtyfxM2fJG7+JHHzJ4lb50nSI8Q2OzCYYbFUxd23j3Pnz3F5sszRgRiG/uAl2jRNoz8doj8d4v3HO1TZNpov2tRsj+6eHrpTUUIBaZ6EEEIIsTXkU8U6JBIJHMeRbkif2elx0zSNxw/0UazUOXjwIOfPnePadHlbl43uNKUU4ws1kskUsWiU/QONFdt2euxEaxI3f5K4+ZPEzZ8kbp0nCxkIsUMUK3W+c+YmM7NzXL58mV2pIHuy4e2uVkfMF22uTJU4evQoe/q6edeJPdtdJSGEEELsUBvJHSSrEGKHiIUDPHGgj3Q6zdDQEJMLNcZz1e2uVtsppRjPVUkkk8RiMQ7uzm53lYQQQgjxiJE+NSF2kN5MjJN7ezkDuK7L6Ogouq6xK/no7m8yna9Trrsc3T9AKhaiO/XWGdYnhBBCiM6QpEeIHWZoVwrHbSw77bgutyYmMHSN7nhgm2u29eqOx+h8le6eHmKxGEeHure7SkIIIYR4BEnSsw7Xrl1bnnS2d+/e7a6OWCM/xm3fQAb7TuLjOg43ZmZRStHziO1of3O2gm5a7B7czZ6eJNlkpOm4H2MnJG5+JXHzJ4mbP0ncOq+jSc/v/u7v8slPfpJoNEqxWOzkpbdEoVBYXlNd+Idf43Z4TxeO66GUQtd1bkxNYbuKgXRou6u2JeYKdXIlm/37DxANBzk6vLqXx6+xe6uTuPmTxM2fJG7+JHHrvI4lPWNjY/zyL/8y/f39LC4uduqyQvjaseFudE1D0zQsy2J0dJS64zHcFUbTHryPz05Wrrlcn6mQzWbJZNIcH+nBMltvyCqEEEIIsVkdW7L6Qx/6EJqmkclk+PKXv9zU0+OXJatd113+34YhH9D84lGI29Wxec7fnGFmdpYb16+Tipjs7Yk8dAPTnch2Pc6NFjGDYY4cOcJQb4rHD/S1/NtHIXZvRRI3f5K4+ZPEzZ8kbpuzkdyhIz09f/AHf8C3vvUtzp8/z6/+6q924pJtIS9Kf3oU4rZvIEMoYPKapmGZJlevXuX8WJH9vRHCAf/cn6cUV6bKKM3g4IGDZBMRTu3bdd+/fxRi91YkcfMniZs/Sdz8SeLWeW1Peqanp3n++ed54YUXGBwcbPflhHhkDXQnCFgG37uoEQyFuHL5MufHigx3hcn6YGU311NcnixTrHkcPnSYRCzMk4cH0H3YWyWEEEIIf2l70vPzP//zHDp0iJ/7uZ9b13nnzp1jaGiIRCKx/LtarcaFCxcASKfT7NnTvGv75cuXKZfLAJw6darp2OzsLGNjYwDs2bOHdDq9fMx1Xc6ePQs0usZWrqJx/fp18vk8AMeOHcM07z62hYUFbt68CUB/fz/d3c2Tsc+cOYNSinA4zMGDB5uO3b59m/n5eQAOHTpEKHR3gnqxWOTq1asA9PT00NfXPPzn/PnzyxPgjh492nRsYmKC6elpAPbt20csFls+Vq1WuXjxIgCZTIbdu3c3nXvp0iUqlQqapnHy5MmmYzMzM4yPjwMwNDREKpVaPuY4DufOnQMgkUgwMjLSdO61a9eWuyGPHz/e9A1HLpfj1q1bAAwMDNDV1dV07unTpwGIRCIcOHCg6ditW7fI5XIAHD58mGDw7upm+Xye69evA9Db28uuXc09CufOncNxHILBIIcPH246Nj4+zszMDAD79+8nGr27d0y5XOby5csAZLPZVcn8xYsXqVarGIbB8ePHm45NT08zMTEBwPDwMMlkcvlYvV7nzTffBCCZTDI8PNx07tWrVykWi6Q1h2AqTeDoUW7cvMnV6VnGZhaJqAKGrpHNZpveN57nLb9GQ6HQqtfS1NTU8vtmcHCwaVJlqVRafi2l0+mmmAPcvHkTz/OwLGvVc5idnV2OeU9vHzdzDhVbNV7rwQAhe56Lbxbp7u6mv7+/6dwLFy5Qq9UwTZNjx441HZucnGRqagqAkZERaSOQNkLaiIalNgLgxIkTTcM85ubmGB0dBRrv82z27ibAnufxxhtvABCLxdi3b19TuTdu3Fiei3vkyBECgbtfsiwuLnLjxg0A+vr66OnpaTr37NmzuK5LKBTi0KFDTcdGR0eZm5sD4MCBA0Qid1dvLJVKXLlyBUDaCGkjAGkjlkgb0bD0Pl2PtiY9f/Znf8Zf/MVf8Nprr6170rXjOKycbqSUwrbt5eOtzlk6vpLnecvHPM9bdXyt5c7Pz2NZ1nJjd2+5947PvLdcpVTL1Tlc110+d+W9rqXc+93rveWuvNd7n2GrcpfutVW81lrudsXmQa+XYrFILpdr+kfKtm0cx2k5/vNBsXnYM1yKTatjDyr33nt9ULmmDj90Yg/nbs5iGAbJRJLz589za6FGb1wnk1ld7tKza1Wu53ktn+1SHZeOtYqN4zh4ntfyGS6Va7uKi5MllBHk0KFDpJIJju1JMT12877P6d5nODc3h67ry7Fba2x2yuvwrdpG5PN5lFLLcduJsVnLe9mPbUQra32GlUplVVt5b51Weti91ut1PM9rOZRnK55hq2f0Vm0jFhcXm5Kend5G+O1zRLvaiFYf3ndyG9Hq/O1qI9arbUlPsVjkU5/6FL/4i79If38/CwsLQOPmoPHNhmVZTZlvU8VMc9UbZmkFq6Xjrc6539J/uq4vH2v14lxLubZtc+vWraak595yWwXMsiyUUi3LNQxj+dyV97qWcu/9eb9yV97rvc+wVblL99qqsVprudsRm6U6tKqTbdssLCxQKpWa/iFfus+HPcMHvQ7vFxvXdVsee1C5997r/cq9e1znsf276E5GOGPoaNpRzp47x+TiIvp0laPhWNNcn6Vn16pcXddbPtulOi4daxUb0zTv21jpuk7Z0RlbdOnqNjh++DCpRJynjw5iai656Qff61IDfP369ab33Fpjs1Neh2/FNsK2baanp5s+PO/E2KzlvezXNmKltTxD27apVqvcunWrqa28t04rPexeA4EAruu25Rl6nrfu981OfB1uto1YMjExQW9v77rKvffnynLlc0R724glrbZw2altxL0/71enldrZRqxX21Zvu3HjxqquyZWeffZZvvKVr/hm9bbTp08vdwWv7PYWO9ejHrdKzebcjRkm5gosLua5cfMG9VqN7niAvlSQoNX595HrKW7PVZnO10in0wyPjBCPhHj66CDxyNo3WH3UY/eokrj5k8TNnyRu/iRx25wdtXrbrl27+MY3vrHq9y+88ALf+ta3ePHFF1eNudzpBgYG7juUR+xcj3rcrCjAfwAACy1JREFUwkGLtx/qZzpX4o1rU8TjcSanJpmcmGSmUCAbs+hPBwlZ7V8pxlOKuYLNaK6K62kMDQ/T29PDrkyMU/t2EVhnHR712D2qJG7+JHHzJ4mbP0ncOq9j+/Qs+fjHP+7bfXqE2Olc1+Py2DzXxnPUHYeZ6WkmJiex63VSEYts3CIVsbZ8fx9PKXJFm9FcjZrtks1mGRgYJBoJc2y4m6FdqYcXIoQQQgixBjuqp0cI0XmGoXN4Txd7+9Jcn8gRClj09PQyNzfLzMwMV6eK6JpGOmaRiVrEQgaWsbEvF5RSFKouuZLNXNHGcT3S6TQHBgaIRCL0pmMcHe4mFt75y2kLIYQQ4tHW8Z6eVqSnR4j2cFyPG5MLXJ/IUa071Go15ubmmJubo1KpABC0DGIhg2jQIGjqWIaGZeiYhoZSjV4cTykcV1G1Pco1l3LdpVRzcT2FFQiQzWbp7uoiHA7TlYxweE8X6Xh4m+9eCCGEEI+ijeQOkvQI8RaglGIuX2FsJs/EfBHbcanV6xQLBYrFIsViiXKljGqxTOVKwWCQSDRKNBIhkUgQi8XQNY2+bJw9vUm6kpGHliGEEEIIsVEyvK3NZKUNf5K4NZZ27EpG6EpGOOEpZhZKzC6WyRWTLBareEo19uRxXex6Hdt2cBwbTdPRDR1d1zF0g1AouLzkZNAyySTC9GVi9KSjWObWL5QgsfMniZs/Sdz8SeLmTxK3zpOkR4i3GF3X6M3E6M00dtj2PMViqUqhXKdmO9Rsl1rdoe64jX16DB1D1zB0nUjIIhkNkogECQak+RBCCCGEP8inlnWIRCI4jnPfjRzFziRxezBd10jHwztyDo7Ezp8kbv4kcfMniZs/Sdw6T+b0CCGEEEIIIXxjI7mDZBVCCCGEEEKIR5okPUIIIYQQQohHmiQ9QgghhBBCiEeazJ5ah1u3bi1POtuzZ892V0eskcTNvyR2/iRx8yeJmz9J3PxJ4tZ50tOzDrlcjvn5eXK53HZXRayDxM2/JHb+JHHzJ4mbP0nc/Eni1nmS9AghhBBCCCEeabJk9TrUajWUUmiaRjAY3O7qiDWSuPmXxM6fJG7+JHHzJ4mbP0ncNmcjuYPM6VkHeVH6k8TNvyR2/iRx8yeJmz9J3PxJ4tZ5O6srRQghhBBCCCG2mCQ9QgghhBBCiEfajhje1mpaked521CTB7t37GA8Ht/Gmoj1kLj5l8TOnyRu/iRx8yeJmz9J3DanVZ7wsGUKdsRCBo7jUCqVtrsaQgghhBBCCB+KRqOY5v37c2R4mxBCCCGEEOKRJkmPEEIIIYQQ4pEmSY8QQgghhBDikbYj5vR4nrdqQpKmaWiatk01EkIIIYQQQuxESqlVCxfouv7AzUl3RNIjhBBCCCGEEO0iw9uEEEIIIYQQjzRJejbhm9/85vIwvJX/vfzyy9tdvbe8YrHI888/T39/P6FQiMcee4w/+qM/2u5qiYeQ99XOVygU+MxnPsMHPvABuru70TSNX/u1X2v5t6+++irve9/7iMVipFIpnnvuOa5du9bZCgtg7XH7+Mc/3vL9d/jw4c5XWvD1r3+df/JP/gmHDx8mGo0yMDDAs88+y/e///1Vfyvvt51jrXGT91vn7IjNSf3u13/913nmmWeafnf8+PFtqo1Y8txzz/HKK6/wwgsvcPDgQb70pS/xsY99jP+/vbsLaaqP4wD+9dmSpmOKm6USGrWIFPdCRd5IKxn2YuCphNhNBN2EkkQwohfdqOgiRkEXRXZRUA3K8kapLsqEbnqhAiOCFr1BIGMzM5sXY//n4tHRnMs9ZeecnX0/4IX/c5Af/vjK+Xn+5yyRSMDj8ShdHs2BuVKvSCSCixcvwm63o7W1FZcuXZr1vDdv3sDlcsHhcODGjRuYnJxEV1cXGhsb8fLlS5SXl8tceX7Ltm8AYDAY8ODBg7Q1kt/58+cRiUTQ2dmJ2tpahMNhBAIBNDQ04N69e9i4cSMA5k1tsu0bwLzJRtBvGxwcFADEzZs3lS6FZhgYGBAAxPXr11PW3W63qKqqEvF4XKHKaC7MlfolEgmRSCSEEEKEw2EBQHR3d6ed19bWJiwWixgbG0uuffjwQSxYsEB4vV65yqUp2fZt9+7dori4WObqKJORkZG0tfHxcbF48WLR1NSUXGPe1CXbvjFv8uH2NtKkvr4+GI1GtLW1pazv2bMHX758wePHjxWqjCj3ZfN2zXg8jv7+fuzYsQMmkym5XlNTgw0bNqCvr+9vl0kz8K2ouWnRokVpa0ajEbW1tfj8+TMA5k2NsukbyYtDzzxob2+HXq+HyWRCc3MzHj16pHRJee/Vq1dYtWoV9PrUHZw2my15nNSNucpt7969QywWS2buZzabDaFQCJOTkwpURtmIxWKoqKiATqfDkiVL0NHRgWg0qnRZNGVsbAzPnz9HXV0dAOYtV8zs2zTmTR58pucPlJSUoLOzEy6XC2azGaFQCKdPn4bL5cLAwACam5uVLjFvRSIRLFu2LG29rKwseZzUibnShumMTWfuZ2VlZRBCYHR0FJWVlXKXRnOw2+2w2+3JZ+iGhoZw5swZ3L9/H0+fPoXRaFS4Qmpvb8fExASOHDkCgHnLFTP7BjBvcuLQM+Xhw4dpD01n8uLFCzgcDjidTjidzuR6Y2MjJElCfX09vF4vL84U9qttHNzioV7MlbYwh7nnwIEDKd+73W44nU7s3LkTPT09acdJXseOHcO1a9dw7tw5rF69OuUY86ZemfrGvMmHQ8+UlStXoqenJ6tzq6urMx4rLS1FS0sLLly4gFgsxrdvKMRsNs96N2f6dvFs/w0j9WKuco/ZbAYw+13VaDSKgoIClJaWyl0W/SZJklBcXMzXxivM7/fjxIkTOHnyJDo6OpLrzJu6ZepbJszb38GhZ0plZSX27t07Lz9LCAGA/1VRUn19PYLBIOLxeMpzPcPDwwD46uNcxFzlluXLl8NgMCQz97Ph4WFYrVYsXLhQgcrodwkh8M8/fBRYKX6/Hz6fDz6fD4cPH045xryp16/69ivM2/zjb3OejY6Oor+/Hw6Hg39gFCRJEr5//45bt26lrF+5cgVVVVVYt26dQpXR72Cuco9er8e2bdtw+/ZtjI+PJ9c/ffqEwcFBbN++XcHq6P/q7e3Fjx8/0NDQoHQpeen48ePw+Xw4evQouru7044zb+o0V98yYd7+Dt7p+QMejwfV1dVYs2YNLBYL3r59i0AggJGREVy+fFnp8vLa5s2b4Xa7sW/fPnz79g1WqxXBYBB3797F1atXodPplC6RMmCucsOdO3cwMTGRvMB6/fo1ent7AQBbtmxBUVER/H4/1q5di5aWFhw6dCj5YYkWiwUHDx5Usvy8NVffwuEwPB4Pdu3aBavVioKCAgwNDeHs2bOoq6ubtx0RlL1AIICuri5s2rQJW7duTdvyNH1hzLypSzZ9+/jxI/MmJyU/JCjXnTp1SjgcDlFSUiJ0Op0oLy8XkiSJJ0+eKF0aif8+BGz//v2ioqJCFBYWCpvNJoLBoNJl0RyYq9xQU1MjAMz69f79++R5z549E01NTaKoqEiYTCbR2toqQqGQcoXnubn6Fo1GhSRJYunSpcJgMIjCwkKxYsUK4fV6xdevX5UuPy+tX78+Y89mXsYxb+qRTd+YN3kVCDG1UZ6IiIiIiEiD+EwPERERERFpGoceIiIiIiLSNA49RERERESkaRx6iIiIiIhI0zj0EBERERGRpnHoISIiIiIiTePQQ0REREREmsahh4iIiIiINI1DDxERERERaRqHHiIiIiIi0jQOPUREREREpGkceoiIiIiISNP+BfSxXh+RKqZeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.021 0.046 0.   ]\n"
     ]
    }
   ],
   "source": [
    "ekf = run_localization(\n",
    "    landmarks[0:2], std_vel=1.e-10, std_steer=1.e-10,\n",
    "    std_range=1.4, std_bearing=.05)\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The estimate quickly diverges from the robot's path after passing the landmarks. The covariance also grows quickly. Let's see what happens with only one landmark:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.271 0.828 0.004]\n"
     ]
    }
   ],
   "source": [
    "ekf = run_localization(\n",
    "    landmarks[0:1], std_vel=1.e-10, std_steer=1.e-10,\n",
    "    std_range=1.4, std_bearing=.05)\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you probably suspected, one landmark produces a very bad result. Conversely, a large number of landmarks allows us to make very accurate estimates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final P: [0.008 0.009 0.001]\n"
     ]
    }
   ],
   "source": [
    "landmarks = array([[5, 10], [10,  5], [15, 15], [20,  5], [15, 10], \n",
    "                   [10,14], [23, 14], [25, 20], [10, 20]])\n",
    "\n",
    "ekf = run_localization(\n",
    "    landmarks, std_vel=0.1, std_steer=np.radians(1),\n",
    "    std_range=0.3, std_bearing=0.1, ylim=(0, 21))\n",
    "print('Final P:', ekf.P.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Discussion\n",
    "\n",
    "I said that this was a real problem, and in some ways it is. I've seen alternative presentations that used robot motion models that led to simpler Jacobians. On the other hand, my model of the movement is also simplistic in several ways. First, it uses a bicycle model. A real car has two sets of tires, and each travels on a different radius. The wheels do not grip the surface perfectly. I also assumed that the robot responds instantaneously to the control input. Sebastian Thrun writes in *Probabilistic Robots* that this simplified model is justified because the filters perform well when used to track real vehicles. The lesson here is that while you have to have a reasonably accurate nonlinear model, it does not need to be perfect to operate well. As a designer you will need to balance the fidelity of your model with the difficulty of the math and the CPU time required to perform the linear algebra. \n",
    "\n",
    "Another way in which this problem was simplistic is that we assumed that we knew the correspondance between the landmarks and measurements. But suppose we are using radar - how would we know that a specific signal return corresponded to a specific building in the local scene? This question hints at SLAM algorithms - simultaneous localization and mapping. SLAM is not the point of this book, so I will not elaborate on this topic. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## UKF vs EKF\n",
    "\n",
    "\n",
    "In the last chapter I used the UKF to solve this problem. The difference in implementation should be very clear. Computing the Jacobians for the state and measurement models was not trivial despite a rudimentary motion model. A different problem could result in a Jacobian which is difficult or impossible to derive analytically. In contrast, the UKF only requires you to provide a function that computes the system motion model and another for the measurement model. \n",
    "\n",
    "There are many cases where the Jacobian cannot be found analytically. The details are beyond the scope of this book, but you will have to use numerical methods to compute the Jacobian. That undertaking is not trivial, and you will spend a significant portion of a master's degree at a STEM school learning techniques to handle such situations. Even then you'll likely only be able to solve problems related to your field - an aeronautical engineer learns a lot about Navier Stokes equations, but not much about modelling chemical reaction rates. \n",
    "\n",
    "So, UKFs are easy. Are they accurate? In practice they often perform better than the EKF. You can find plenty of research papers that prove that the UKF outperforms the EKF in various problem domains. It's not hard to understand why this would be true. The EKF works by linearizing the system model and measurement model at a single point, and the UKF uses $2n+1$ points.\n",
    "\n",
    "Let's look at a specific example. Take $f(x) = x^3$ and pass a Gaussian distribution through it. I will compute an accurate answer using a monte carlo simulation. I generate 50,000 points randomly distributed according to the Gaussian, pass each through $f(x)$, then compute the mean and variance of the result. \n",
    "\n",
    "The EKF linearizes the function by taking the derivative to find the slope at the evaluation point $x$. This slope becomes the linear function that we use to transform the Gaussian. Here is a plot of that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "actual mean=1.30, std=1.13\n",
      "EKF    mean=1.00, std=0.95\n"
     ]
    }
   ],
   "source": [
    "import kf_book.nonlinear_plots as nonlinear_plots\n",
    "nonlinear_plots.plot_ekf_vs_mc()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The EKF computation is rather inaccurate. In contrast, here is the performance of the UKF:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "actual mean=1.30, std=1.13\n",
      "UKF    mean=1.30, std=1.08\n"
     ]
    }
   ],
   "source": [
    "nonlinear_plots.plot_ukf_vs_mc(alpha=0.001, beta=3., kappa=1.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can see that the computation of the UKF's mean is accurate to 2 decimal places. The standard deviation is slightly off, but you can also fine tune how the UKF computes the distribution by using the $\\alpha$, $\\beta$, and $\\gamma$ parameters for generating the sigma points. Here I used $\\alpha=0.001$, $\\beta=3$, and $\\gamma=1$. Feel free to modify them to see the result. You should be able to get better results than I did. However, avoid over-tuning the UKF for a specific test. It may perform better for your test case, but worse in general."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
